CN112488800A - Network-based petroleum operation data processing method and device and storage medium - Google Patents
Network-based petroleum operation data processing method and device and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a network-based petroleum operation data processing method, a device and a storage medium, wherein the method comprises the following steps: receiving petroleum operation data information sent by a client through the Internet or a virtual private network, wherein the client is a user side and/or a refueling station side; carrying out safety inspection on the petroleum operation data, intercepting the petroleum operation data if the petroleum operation data contains dangerous information, and otherwise, releasing the petroleum operation data; transmitting the released petroleum operation data to a processing server through an NAT gateway and a router for processing; and programming the data processed by the processing server by using a structured query language and storing the data into the database server. Therefore, the safety of the petroleum operation data can be guaranteed, and meanwhile, the processing speed of the petroleum operation data can be increased.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a network-based petroleum operation data processing method, a network-based petroleum operation data processing device and a storage medium.
Background
With the development of society, the services of gas stations are correspondingly added on some maps, and some services aiming at the gas stations are developed.
However, during the operation of the gas station, some interactive operation data at the user end or the gas station end cannot be processed and stored well.
Disclosure of Invention
In view of the above problems, the present invention provides a method, an apparatus, and a storage medium for processing petroleum operation data based on a network, so as to overcome the technical problem in the prior art that interactive operation data of some clients or fueling station terminals cannot be processed and stored well in the fueling station operation process.
According to a first aspect of the invention, a network-based oil operation data processing method is provided, comprising the following steps:
receiving petroleum operation data information sent by a client through the Internet or a virtual private network, wherein the client is a user side and/or a refueling station side;
carrying out safety inspection on the petroleum operation data, intercepting the petroleum operation data if the petroleum operation data contains dangerous information, and otherwise, releasing the petroleum operation data;
transmitting the released petroleum operation data to a processing server through an NAT gateway and a router for processing;
and programming the data processed by the processing server by using a structured query language and storing the data into the database server.
Further, if the oil operation data is issued oil information sent from the refueling station, the released oil operation data is transmitted to a processing server through an NAT gateway and a router for processing, and the method specifically includes:
transmitting the released oil product information to the processing server through an NAT gateway and a router;
the processing server inputs the issued oil product information into an oil product type identification model for processing, and outputs the issued oil product type corresponding to the issued oil product information, wherein the oil product type identification model is obtained by training a neural network by using sample oil product information which is marked with oil product types in advance;
the processing server searches a corresponding target auditing standard in a memory according to the issued oil product category, wherein the auditing standard corresponding to each oil product category is stored in the memory in advance;
the processing server checks various parameters of the issued oil product information according to the target auditing standard, and if the checking is successful, the issued oil product information is used as processed data;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and pushing the programmed data stored in the database server to an account platform corresponding to the refueling station terminal for release.
Further, before the processing server inputs the published oil product information into an oil product type identification model for processing and outputs the published oil product type corresponding to the published oil product information, the method specifically includes:
obtaining sample oil information of a preset quantity, and adding a corresponding oil type label to each sample oil information, wherein each sample oil information comprises a plurality of oil information data;
an oil product identification initial neural network with an oil product identification input layer, N oil product identification hidden layers and an oil product identification output layer is constructed in advance, wherein the construction number N of the oil product identification hidden layers is more than or equal to the maximum value X of the number of oil product information data in the sample oil product information;
inputting the sample oil product information from an oil product identification input layer, and processing the sample oil product information through the N oil product identification hidden layers, wherein the first oil product identification hidden layer receives data content output from the oil product identification input layer, and the rest oil product identification hidden layers receive data content output after the previous oil product identification hidden layer is processed;
the last oil product identification hidden layer outputs the processing result data to the oil product identification output layer so that the oil product identification output layer can determine the corresponding output oil product type according to the processing result data;
judging whether the output oil type is the same as the corresponding oil type label, if so, training the next sample oil information, and if not, adjusting the parameters of each oil identification hidden layer to ensure that the output oil type is the same as the corresponding oil type label;
and taking the oil product identification initial neural network after the sample oil product information is completely trained as an oil product identification model, and storing the oil product identification model into a processing server.
Further, if the petroleum operation data is information to be released of petroleum knowledge sent from the fueling station side and/or the user side, the released petroleum operation data is transmitted to a processing server through an NAT gateway and a router for processing, and the method specifically includes:
transmitting the released petroleum knowledge to-be-released information to the processing server through the NAT gateway and the router;
the processing server inputs the information to be published of the petroleum knowledge into a knowledge category identification model for processing, and outputs the knowledge category to be published corresponding to the information to be published of the petroleum knowledge, wherein the knowledge category identification model is obtained by training a neural network by using sample petroleum knowledge information which is labeled with the knowledge category in advance;
the processing server marks the information to be published of the petroleum knowledge by using the type of the knowledge to be published, and takes the marked information to be published of the petroleum knowledge as processed data;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and pushing the programmed data stored in the database server to an account platform corresponding to the refueling station terminal and/or the user terminal for issuing.
Further, before the processing server inputs the information to be published of the petroleum knowledge into a knowledge category identification model for processing and outputs a knowledge category to be published corresponding to the information to be published of the petroleum knowledge, the method specifically includes:
acquiring a preset number of sample petroleum knowledge information, and adding a corresponding knowledge category label to each sample petroleum knowledge information;
pre-constructing a knowledge identification initial neural network with a knowledge identification input layer, M knowledge identification hidden layers and a knowledge identification output layer, wherein each knowledge identification hidden layer correspondingly identifies the coincidence probability of a knowledge category, and the construction number M of the knowledge identification hidden layers is more than or equal to the maximum value Q of the category number of the knowledge categories in the sample petroleum knowledge information;
inputting the sample petroleum knowledge information from a knowledge identification input layer, and extracting key words from the sample petroleum knowledge information by the knowledge identification input layer;
the knowledge identification input layer respectively inputs the extracted keywords into each knowledge identification hidden layer for processing, and each knowledge identification hidden layer correspondingly outputs the probability P belonging to the corresponding knowledge category1，P2，……，PMAnd respectively sending the data to the knowledge identification output layer;
the knowledge identification output layer screens out the knowledge category corresponding to the maximum value of the probability of the knowledge category as an output knowledge category, judges whether the output knowledge category is the same as the corresponding knowledge category label or not, trains the next sample petroleum knowledge information if the output knowledge category is the same as the corresponding knowledge category label, otherwise, trains the next sample petroleum knowledge information after adjusting the parameters of the knowledge identification hidden layer corresponding to the knowledge category label to make the probability of the processed output knowledge category 100%;
and taking the knowledge identification initial neural network after the sample petroleum knowledge information is completely trained as a knowledge category identification model, and storing the knowledge category identification model into a processing server.
Further, if the oil operation data information is order data of successful transaction of the refueling station end in a set time period, the released oil operation data is transmitted to a processing server through an NAT gateway and a router for processing, and the method specifically includes:
transmitting the order data of successful released transaction to the processing server through the NAT gateway and the router;
the processing server calculates the cost amount of each successful transaction order data according to the petroleum type and the petroleum amount in the successful transaction order data; calculating corresponding profit amount according to the cost amount and the transaction amount of each successful order data, and establishing a coordinate system by taking the profit amount as a vertical axis and corresponding time as a horizontal axis;
the processing server analyzes the coordinate system, determines a corresponding operation state, and takes the operation state as processed data, specifically: if the coordinate system is an integral ascending trend, determining that the account corresponding to the refueling station end belongs to ascending operation, if the coordinate system is an up-and-down fluctuation trend, determining that the account corresponding to the refueling station end belongs to stable operation, and if the coordinate system is an integral descending trend, determining that the account corresponding to the refueling station end belongs to descending operation;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and pushing the programmed data stored in the database server to the refueling station end for display.
Further, if the oil operation data is an oil product inspection instruction sent from the user side and/or the refueling station side, the passing oil operation data is transmitted to the processing server through the NAT gateway and the router for processing, and the method specifically includes:
transmitting the released oil product inspection instruction to the processing server through an NAT gateway and a router, wherein the oil product inspection instruction contains the petroleum type;
the processing server extracts the oil type in the oil product inspection instruction, and at least one inspection station to be determined with the oil type inspection qualification is searched from a map;
the processing server acquires the position information of the user side and/or the refueling station side, and searches for a determined inspection station belonging to the same city level as the position information from at least one inspection station to be determined; if a plurality of the found determined inspection stations exist, arranging the inspection stations according to the sequence of the distance from the position information to the far position, and then sending the inspection stations to the user side and/or the refueling station side so that the user side and/or the refueling station side can select a target inspection station from the plurality of the determined inspection stations;
the processing server receives a target inspection station and delivery time sent by the released user side and/or the released refueling station side through the Internet or a virtual private network, acquires whether delivery service corresponding to the petroleum type of the target inspection station in the delivery time is saturated or not, generates a delivery refusal instruction to be sent to the user side and/or the refueling station side if the delivery service is saturated, so that the user side and/or the refueling station side can determine the target inspection station again, packages the oil product inspection instruction and the delivery time if the delivery service is not saturated, and takes the packaged data as processed data;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and sending the programmed data stored in the database server to the target inspection station.
According to a second aspect of the present invention, there is provided a network-based oil operation data processing apparatus comprising:
the system comprises a receiving module, a data processing module and a data processing module, wherein the receiving module is used for receiving petroleum operation data information sent by a client through the Internet or a virtual private network, and the client is a user side and/or a refueling station side;
the inspection module is used for carrying out safety inspection on the petroleum operation data, intercepting the petroleum operation data if the petroleum operation data contains dangerous information, and releasing the petroleum operation data if the petroleum operation data does not contain dangerous information;
the processing module is used for transmitting the released petroleum operation data to the processing server through the NAT gateway and the router for processing;
and the storage module is used for programming the data processed by the processing server by using a structured query language and storing the data into the database server.
According to a third aspect of the present invention, an electronic device is provided, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the network-based oil operation data processing method according to the first aspect when executing the computer program.
According to a fourth aspect of the present invention, a storage medium is proposed, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the network-based oil run data processing method of the first aspect.
The network-based petroleum operation data processing method, device and storage medium provided by the embodiment of the invention have the following beneficial effects:
according to the technical scheme, the petroleum operation data sent by the user side and/or the refueling station side through the Internet or the virtual private network are subjected to security check, no dangerous information is determined, the petroleum operation data are transmitted to the processing server through the NAT gateway and the router to be further processed according to the specific content of the petroleum operation data, and the processing result is programmed by using the structured query language and is stored in the database server. Therefore, the safety of the petroleum operation data can be guaranteed, and meanwhile, the processing speed of the petroleum operation data can be increased.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
The invention will be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a network-based oil-run data processing method according to an embodiment of the present invention;
FIG. 2 is a block diagram of a fueling station-based oil data processing apparatus according to an embodiment of the present invention;
fig. 3 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
As shown in fig. 1, this embodiment provides a network-based oil operation data processing method, which is applicable to a server side, where the server side belongs to a service platform that is set up in advance and performs centralized processing on oil filling data sent from a user side and/or an oil filling station side, and the user side and the oil filling station side need to install corresponding APPs in advance on the user side and the oil filling station side or install corresponding applets in instant messaging, in order to perform oil operation data processing by using the service platform. The server is a generic name of the following servers.
The method comprises the following steps:
The Virtual Private Network (VPN) can establish a Private Network on a public Network to perform encrypted communication.
The corresponding oil operation data can be message data, instruction data, volume data and the like.
And 102, carrying out safety check on the petroleum operation data, intercepting the petroleum operation data if the petroleum operation data contains dangerous information, and otherwise, releasing the petroleum operation data.
Wherein, the petroleum operation data is firstly input into the safe operation server. Firstly, statistical analysis is carried out on the petroleum operation data by using Statistical Analysis Software (SAS), and if the analysis is unqualified, the petroleum operation data is directly intercepted, and the transmission of the petroleum operation data is forbidden. And if the analysis is qualified, performing anomaly detection processing by using an anomaly detection protocol. And if the abnormality is detected, directly intercepting the petroleum operation data, forbidding the transmission of the petroleum operation data, and if the abnormality is not detected, releasing the petroleum operation data.
And 103, transmitting the released petroleum operation data to a processing server through the NAT gateway and the router for processing.
The released petroleum operation data is firstly input into a Network Address Translation (NAT) gateway, Network Address Translation is carried out, the released petroleum operation data is transmitted into a processing server through a router after the released petroleum operation data is converted into a website capable of entering the processing server.
And 104, programming the data processed by the processing server by using a structured query language and storing the data into the database server.
The Structured Query Language (SQL), a database Query and programming Language, is used to access data, Query, update, and manage the relational database system, and is used to program the processed data and edit the data into a Structured Query Language that can be recognized by the processing server, so as to speed up the processing speed of the processing server.
By the scheme, the petroleum operation data sent by the user side and/or the refueling station side through the Internet or the virtual private network is subjected to security check, no dangerous information is determined, the petroleum operation data is transmitted to the processing server through the NAT gateway and the router to be further processed according to the specific content of the petroleum operation data, and the processing result is programmed by using a structured query language and is stored in the database server. Therefore, the safety of the petroleum operation data can be guaranteed, and meanwhile, the processing speed of the petroleum operation data can be increased.
In a specific embodiment, if the oil operation data is issued oil product information sent from the fueling station, step 103 specifically includes:
and step A1, transmitting the released oil product information to a processing server through a NAT gateway and a router.
Wherein, the published oil product information comprises at least one of the following: oil product name, oil product composition, oil product unit price, oil product total amount, oil product production place and oil product processing manufacturer.
And the user of the gas station inputs corresponding oil product information to be published through the gas station terminal for later verification, and the oil product information is published through a network after the verification is passed.
In addition, before receiving the published oil product information sent by the refueling station terminal, a corresponding APP is installed at the refueling station terminal in advance or a corresponding small program is loaded in instant messaging, a refueling station account is established in advance, a corresponding user role is selected, and a personal user or a refueling station user can be selected.
When a gas station user is selected, an account registration interface is popped up. The method comprises the steps of inputting a name and a password of the refueling station, packaging and sending the name and the password of the refueling station and the selected role of the refueling station to a server, matching a corresponding interface of the refueling station by the server according to the role of the refueling station, and establishing a corresponding storage database for a corresponding account number of the refueling station so as to store data information of the account number of the refueling station. The data of each gas station user in the server are correspondingly stored in a gas station user memory, and the gas station user memory comprises a storage database corresponding to each gas station account.
Therefore, when a person in the gas station logs in again through the gas station terminal, an account login instruction is sent to the server, and the account login instruction comprises role authority information, an account name, a password and some basic information corresponding to the gas station terminal.
And after the server receives the account login instruction, if the role authority information is the gas station user, calling the relevant display information in the storage database corresponding to the gas station account from the gas station user storage. And sending the corresponding display information to the corresponding refueling station end for display.
And step A2, the processing server inputs the published oil product information into an oil product type identification model for processing, and outputs the published oil product type corresponding to the published oil product information, wherein the oil product type identification model is obtained by training a neural network by using sample oil product information which is marked with oil product types in advance.
The oil product type identification model is obtained by learning and training a neural network according to a plurality of groups of sample oil product information of oil product types marked in advance.
The oil product identification input layer of the oil product type identification model comprises a plurality of input ports, and each input port correspondingly inputs one item of data in the published oil product information. The number of the input ports is more than or equal to the number of the items with the most data in the sample oil product information. The method is used for ensuring that each item of data in the published oil product information can be input and processed simultaneously. The oil product identification input layer carries out data conversion processing on the issued oil product information and converts the issued oil product information into code data so that an oil product identification hidden layer of an oil product type identification model can process the code data, and finally the issued oil product type corresponding to the issued oil product information is obtained and output through the oil product identification output layer.
Step A3, the processing server searches the corresponding target auditing standard in the memory according to the issued oil product category, wherein the auditing standard corresponding to each oil product category is stored in the memory in advance.
And step A4, the processing server checks various parameters of the issued oil product information according to the target auditing standard, and if the checking is successful, the issued oil product information is used as processed data.
Then, after step 104, further comprising:
and 105A, pushing the programmed data stored in the database server to an account platform corresponding to the refueling station terminal for issuing.
In the above scheme, the target audit standard can be used to audit whether the oil product name in the published oil product information is correct, whether the corresponding oil product composition is within the range of each composition corresponding to the published oil product category, whether the oil product unit price meets the unit price interval corresponding to the changed published oil product category issued by the official, and whether the oil product production place and the like in the published oil product information can be found in each oil product production place of the published oil product category stored in advance. After all the parameters in the issued oil product information meet the target auditing standard, the successful verification can be determined, otherwise, the verification is determined to be unsuccessful, and reminding information is generated and sent to the refueling station terminal, so that the staff of the refueling station can see the corresponding reminding information to modify the issued oil product information or cancel the oil product issuance.
By the scheme, the issued oil type corresponding to the issued oil information can be determined according to the issued oil information sent by the refueling station terminal by utilizing the pre-constructed oil type identification model, so that the corresponding target auditing standard can be searched from the memory according to the issued oil type, the issued oil information can be audited according to the target auditing standard, and the issued oil information can be issued after the auditing is successful, so that the correctness of the issued oil information can be improved, the later modification is avoided, and the operation is simple and rapid.
In a specific embodiment, before step a2, the method specifically includes:
step A21, obtaining sample oil product information of a preset quantity, and adding a corresponding oil product type label for each sample oil product information, wherein each sample oil product information contains a plurality of oil product information data.
Step A22, an oil product identification initial neural network with an oil product identification input layer, N oil product identification hidden layers and an oil product identification output layer is constructed in advance, wherein the construction number N of the oil product identification hidden layers is more than or equal to the maximum number X of oil product information data in sample oil product information.
Step A22, inputting sample oil product information from an oil product identification input layer, and processing the sample oil product information through N oil product identification hidden layers, wherein the first oil product identification hidden layer receives data content output from the oil product identification input layer, and the rest oil product identification hidden layers receive data content output after the last oil product identification hidden layer is processed.
And step A23, the last oil product identification hidden layer outputs the processing result data to the oil product identification output layer, so that the oil product identification output layer determines the corresponding output oil product type according to the processing result data.
And A24, judging whether the output oil type is the same as the corresponding oil type label, if so, training the next sample oil information, and if not, adjusting the parameters of each oil identification hidden layer to ensure that the output oil type is the same as the corresponding oil type label.
And step A25, taking the oil product identification initial neural network after the sample oil product information is completely trained as an oil product identification model, and storing the oil product identification model into a processing server.
In the scheme, the oil product identification input layer comprises a plurality of input ports, and each input port corresponds to one data item in the input sample oil product information. The number of the input ports is more than or equal to the number of the items with the most data in the sample oil product information. Is used to ensure that each item of data in the sample oil product information can be input and processed simultaneously. The oil product identification input layer carries out data conversion processing on the sample oil product information and converts the sample oil product information into code data so that the oil product identification hidden layer can process the code data,
each sample oil information includes one or more of oil name, oil composition, oil unit price, oil total, oil production location, and oil processing manufacturer. The number of input ports takes the number of items with the most data in the sample oil information as a set number. Or the number of items (for example, 5 items) that is the most than the data in the sample oil information as the set number of input ports.
The number of the oil product identification hidden layers is consistent with that of the input ports, each item of data in the sample oil product information is correspondingly processed by the corresponding oil product identification hidden layer, then a processing result is transmitted to the next oil product identification hidden layer for processing, the next oil product identification hidden layer combines the processing result of the previous oil product identification hidden layer with the processing result of the data in the sample oil product information needing to be processed by the oil product identification hidden layer, then the next oil product identification hidden layer is transmitted to the next oil product identification hidden layer, and the like until the last oil product identification hidden layer transmits the final processing result to the oil product identification output layer, and the oil product identification output layer converts the processing result into corresponding character information of the output oil product type and outputs the character information.
If the output oil type is the same as the corresponding oil type label, the next sample oil information is directly processed without processing, if the output oil type is different from the corresponding oil type label, the output result of the oil identification initial neural network is proved to be incorrect, the oil identification initial neural network needs to be adjusted, and the parameters of each oil identification hidden layer can be manually adjusted according to experience until the output result is the same as the oil type label. Or calculating a corresponding loss function according to the output oil type and the oil type label, automatically adjusting each oil identification hidden layer according to the loss function, and then processing the sample oil information again by using the adjusted oil identification initial neural network until the output result is consistent with the oil type label.
After all sample oil product information is trained, detecting the trained oil identification initial neural network by using a preset amount of detection sample data, judging the accuracy rate of the identification result, if the accuracy rate exceeds a corresponding threshold value, proving that the trained oil identification initial neural network meets the standard and can be used as an oil identification neural network model, if the accuracy rate is less than the corresponding threshold value, reselecting the sample oil product information, and training the oil identification initial neural network again until the accuracy rate of the obtained oil identification initial neural network exceeds the corresponding threshold value.
And using the final oil identification initial neural network as an oil category identification model.
Through the scheme, the oil type identification model obtained by training the neural network can be utilized, and when the issued oil information is subjected to oil type identification, the accuracy of the result of the oil type identification is further improved.
In a specific embodiment, if the petroleum operation data is information to be released of petroleum knowledge sent from the fueling station side and/or the user side, step 103 specifically includes:
and step B1, transmitting the released information to be released of the petroleum knowledge to a processing server through the NAT gateway and the router.
And step B2, the processing server inputs the information to be released of the petroleum knowledge into a knowledge category identification model for processing, and outputs the knowledge category to be released corresponding to the information to be released of the petroleum knowledge, wherein the knowledge category identification model is obtained by training a neural network by using sample petroleum knowledge information with the knowledge category marked in advance.
And step B3, the processing server marks the information to be released of the petroleum knowledge by using the type of the knowledge to be released, and takes the marked information to be released of the petroleum knowledge as processed data.
Then, after step 104, further comprising:
and 105B, pushing the programmed data stored in the database server to an account platform corresponding to the refueling station end and/or the user end for issuing.
In the above scheme, a user of the gas station or a personal user can correspondingly release some knowledge about the oil, such as safety knowledge during refueling, or the working principle of the vehicle engine, or a change message about the oil price in other countries, and the like, through a refueling station end or a user end.
The knowledge type of the information to be published of the petroleum knowledge needs to be processed by a knowledge type identification model, if the output information to be published is different in type, the information to be published of the petroleum knowledge can be marked with corresponding knowledge type labels, and the marked petroleum knowledge publishing information is used for retraining the knowledge type identification model. And enabling the output result of the retrained knowledge type identification model to meet the requirement.
And then, after the knowledge category to be released is obtained, if the account platform corresponding to the refueling station end and/or the user end has the knowledge category to be released, adding the information to be released of the petroleum knowledge into the knowledge category to be released, and if the information does not have the knowledge category to be released, establishing a new issuing knowledge category, and then adding the information to be released of the petroleum knowledge into the knowledge category to be released.
Through the scheme, the petroleum knowledge information to be published can be classified and processed by means of the knowledge category identification model, the petroleum knowledge information is prevented from being looked up well when the quantity of the petroleum knowledge information is large, a look-up person can look up the petroleum knowledge information conveniently, the use is convenient, and a petroleum knowledge interface can be tidier.
In a specific embodiment, before step B2, the method specifically includes:
and step B21, acquiring a preset number of sample petroleum knowledge information, and adding a corresponding knowledge category label for each sample petroleum knowledge information.
Wherein knowledge category labels include, but are not limited to, at least one of: security category, news category, usage category, basic knowledge category, and the like.
And step B22, pre-constructing a knowledge identification initial neural network with a knowledge identification input layer, M knowledge identification hidden layers and a knowledge identification output layer, wherein each knowledge identification hidden layer correspondingly identifies the coincidence probability of a knowledge category, and the construction number M of the knowledge identification hidden layers is more than or equal to the maximum value Q of the category number of the knowledge categories in the sample petroleum knowledge information.
The knowledge identification input layer carries out data conversion processing on the sample petroleum knowledge information and converts the sample petroleum knowledge information into code data, so that the knowledge identification hidden layer can process the code data.
And step B23, inputting the sample petroleum knowledge information from the knowledge identification input layer, and extracting keywords from the sample petroleum knowledge information by the knowledge identification input layer.
The knowledge identification input layer deletes the virtual words, the adjectives, the punctuations and the like in the sample petroleum knowledge information, divides the remaining characters into words, and takes each divided word as an extracted keyword.
Step B24, the knowledge identification input layer inputs the extracted key words into each knowledge identification hidden layer for processing, and each knowledge identification hidden layer correspondingly outputs the probability P belonging to the corresponding knowledge category1，P2，……，PMAnd respectively sent to the knowledge identification output layer.
The knowledge identification input layer inputs the extracted keywords into each knowledge identification hidden layer at the same time for processing, each knowledge identification hidden layer performs simultaneous processing, and the probability obtained by the processing is sent to the knowledge identification output layer.
And step B25, the knowledge identification output layer screens out the knowledge type corresponding to the maximum value of the probability of the knowledge type as the output knowledge type, judges whether the output knowledge type is the same as the corresponding knowledge type label, if so, trains the next sample petroleum knowledge information, otherwise, adjusts the parameters of the knowledge identification hidden layer corresponding to the knowledge type label to make the probability of the output knowledge type after processing 100%, and trains the next sample petroleum knowledge information.
If the maximum value of the probabilities of the knowledge categories screened by the knowledge identification output layer is two, the two output knowledge categories are correspondingly output, and the parameters of the knowledge identification hidden layer corresponding to the knowledge category labels are adjusted to enable the probability of the processed output knowledge categories to be 100%, and then the next sample petroleum knowledge information is trained.
And step B26, taking the knowledge identification initial neural network after the sample petroleum knowledge information is completely trained as a knowledge type identification model, and storing the knowledge type identification model into a processing server.
After all sample petroleum knowledge information is trained, detecting the trained knowledge identification initial neural network by using a preset amount of detection sample data, judging the accuracy rate of the identification result, if the accuracy rate exceeds a corresponding threshold value, proving that the trained knowledge identification initial neural network meets the standard and can be used as a knowledge type identification model, if the accuracy rate is less than the corresponding threshold value, reselecting the information sample data, and training the knowledge identification initial neural network again until the accuracy rate of the obtained knowledge identification initial neural network exceeds the corresponding threshold value.
And identifying the initial neural network as a knowledge category identification model by using the final knowledge.
Through the scheme, the knowledge type identified by the knowledge type identification model can be more accurate, the petroleum knowledge information is not required to be classified manually, and the use is convenient.
In a specific embodiment, if the oil operation data information is order data of a successful transaction of the fueling station end within a set time period, step 103 specifically includes:
and step C1, transmitting the order data of successful released transaction to the processing server through the NAT gateway and the router.
Step C2, the processing server calculates the cost amount of each successful trade order data according to the petroleum type and the petroleum amount in the successful trade order data. And calculating corresponding profit amount according to the cost amount and the transaction amount of each successful order data, and establishing a coordinate system by taking the profit amount as a vertical axis and corresponding time as a horizontal axis.
Step C3, the processing server analyzes the coordinate system, determines the corresponding operation status, and takes the operation status as the processed data, specifically: and if the coordinate system is an overall ascending trend, determining that the account corresponding to the refueling station end belongs to ascending type operation, if the coordinate system is an upward and downward fluctuating trend, determining that the account corresponding to the refueling station end belongs to stable type operation, and if the coordinate system is an overall descending trend, determining that the account corresponding to the refueling station end belongs to descending type operation.
Then, after step 104, further comprising:
and 105, pushing the programmed data stored in the database server to a refueling station end for displaying.
By the scheme, the corresponding coordinates can be established according to the profit condition of the historical order data of the gas station, and the operation condition of the account corresponding to the gas station terminal is determined according to the trend displayed on the coordinates. And then inform the gas station in time to carry out corresponding operation adjustment, reduce the condition that causes bankruptcy because the gas station is poor to operate.
In addition, if the gas station is determined to belong to the descending type operation, some articles or strategies about the operation of the gas station can be acquired from the network and pushed to the gas station end together for the responsible person of the gas station to check. Thereby improving the operation strategy of the gas station.
In a specific embodiment, if the oil operation data is an oil inspection instruction sent from the user side and/or the fueling station side, step 103 specifically includes:
and D1, transmitting the released oil product inspection instruction to a processing server through the NAT gateway and the router, wherein the oil product inspection instruction contains the petroleum type.
And D2, the processing server extracts the oil type in the oil product inspection instruction, and searches at least one inspection station to be determined which is qualified for oil type inspection from the map.
And D3, the processing server acquires the position information of the user terminal and/or the refueling station terminal, and searches for a determined checkpoint belonging to the same city level as the position information from at least one checkpoint to be determined. And if a plurality of searched determined inspection stations exist, arranging the inspection stations according to the sequence of the distance from the inspection station to the position information, and then sending the inspection stations to the user side and/or the refueling station side so that the user side and/or the refueling station side can select a target inspection station from the plurality of determined inspection stations.
And D4, the processing server receives the target inspection station and the delivery time sent by the released user side and/or the refueling station side through the Internet or the virtual private network, acquires whether the delivery service corresponding to the petroleum type of the target inspection station in the delivery time is saturated, generates a delivery refusal instruction to be sent to the user side and/or the refueling station side if the delivery service is saturated, so that the user side and/or the refueling station side can re-determine the target inspection station, packs the oil product inspection instruction and the delivery time if the delivery service is not saturated, and takes the packed data as the processed data.
Then, after step 104, further comprising:
step 105D, sending the programmed data stored in the database server to the target inspection station.
In the above solution, if the client is the fueling station, the fueling station may need to put some branded oil or some premium oil on the shelf, but the oil quality of the branded oil or the premium oil needs to be verified and confirmed by the inspection station. However, since the corresponding inspection service of the inspection station may be busy, in order to facilitate this process and avoid time waste, the fueling station end may perform the search and determination through the server.
And if the refueling station terminal wants to check the oil K of a certain type, sending an oil checking instruction to the server.
The map is a geographical position map of each inspection station with oil inspection qualification. And marking the corresponding oil type of the inspection qualification on each inspection station in the map in advance, so that the corresponding search can be carried out in the map according to the oil type in the oil inspection instruction.
For a certain fueling station end, only the check result from the local check station may be valid, so that the check station corresponding to the local city level organization needs to be correspondingly searched as the determined check station of the fueling station end. One or more of the identified verification checkpoints may be found.
In addition, if the corresponding definite inspection station can not be found in the same city level, the definite inspection station of province level is searched in an enlarged range, and if the corresponding definite inspection station can not be found in the province level, the definite inspection station in the whole country is searched.
And if one found check station is determined, directly sending the check station to the client side for the user of the gas station to confirm at the client side. If a plurality of check stations are searched for, the user of the gas station needs to select according to the actual situation.
And after the oil product inspection instruction is sent to the target inspection station by the processing server, generating a corresponding unique determination code, and integrating the mailing information of the target inspection station and the unique determination code and then sending the integrated mailing information to the client. Therefore, the user of the gas station can mark the oil sample with the unique determination code and mail the oil sample to the target inspection station according to the corresponding mail information. And after receiving the oil product sample, the target inspection station judges whether the corresponding unique determination code is correct or not, if so, detects the oil product sample and issues a corresponding detection report. And uploading the detection report carrying the unique determination code to a processing server, determining the corresponding client of the gas station user by the processing server according to the unique determination code, and sending the detection report to the client for query and display.
Through the scheme, a user of the gas station does not need to arrive at the inspection station to carry out oil product inspection on site, so that the whole oil product inspection procedure is more convenient and faster.
In a specific embodiment, if the petroleum operation data is a sub-account application instruction sent from the fueling station side corresponding to the general account, the specific processing procedure of the processing server in step 103 includes:
step E1, receiving a sub-account application instruction sent by the refueling station terminal corresponding to the total account, wherein the sub-account application instruction comprises: and the terminal identification code of the refueling station end corresponding to the sub-account, the application address of the sub-account and the service item of the sub-account.
And E2, checking the sub-account application instruction, and determining whether each item of information in the sub-account application instruction is real.
And E3, if the audit is successful, constructing a sub-database corresponding to the sub-account in the account management database of the total account, so that the sub-account can store the successful service item information in the sub-database, and if the audit is failed, generating an application failure instruction and feeding the application failure instruction back to the refueling station end corresponding to the total account, so that the refueling station end corresponding to the total account can modify or cancel the sub-account application instruction.
In the above scheme, if a gas station wants to set up a subordinate gas station, the gas station can be set up by the above steps, a total account of the gas station can set up a plurality of sub-accounts, and the total account can call up various data of the corresponding sub-accounts by querying the sub-database.
In addition, statistics can be carried out on the daily, weekly, quarterly or yearly order data of each sub-account, and the statistical result is sent to the total account. And each sub-account can also be provided with a corresponding sub-account, and after the data of each sub-account is counted, summarized and sent to the sub-account, the sub-account summarizes the data of the sub-account and each sub-account and sends the data to the total account.
Therefore, if the gas station wants to expand the operation range, the subaccount is established, and the setting can be carried out through the scheme, so that diversified services are provided for a gas station user, and the gas station can conveniently expand the scale.
Based on the scheme of the above embodiment, further description is made, and the specific scheme is as follows:
no matter at the fueling station end or at the user end, if the function of the scheme of the application needs to be used, a pre-established account needs to be logged in, and a corresponding account login instruction is used as petroleum operation data, then the specific processing process of the processing server in step 103 includes:
step F1, receiving an account login command sent by the client, and authenticating the account login command with the corresponding account information in the database.
In the step, a personal user or a gas station user wants to log in an account of the user, corresponding account information and an account password need to be input in an APP (application) or an embedded applet of a client, and the client maps and associates the account information and the account password to form an account login instruction and sends the account login instruction to a server.
After receiving the account login instruction, the server extracts the account information in the account login instruction, searches a corresponding storage database according to the account information, extracts an account password, compares the account password with the password stored in the storage database, and if the comparison is successful, the authentication is successful.
Step F2, after the authentication is successful, acquiring a corresponding Token signature, and combining the Token signature with the account login instruction to generate Token data.
The Token (Token, mark) is stored in a storage database of the server, unique Token signature data belonging to the account is stored in the storage database of the server, and the Token signature and the account login instruction are integrated together to generate the Token data.
Step F3, generating JWT data according to the Token data, and feeding back the JWT data to the client for the client to determine corresponding role authority information according to the JWT data.
Among them, JWT (Json web token, network data tagging specification). The JWT data includes a header, a payload, and a signature, wherein the header is a corresponding file type, the payload is a data object (e.g., oil order data information of a user), and the like, and the signature is Token data, which is arranged as JWT data, and then the JWT data is transmitted to a corresponding client.
After receiving the JWT data, the APP or applet in the client extracts Token data therein and stores the Token data in a cookie repository in the client. Wherein the cookie repository is a database stored on the user's local terminal. And generating a resource access request through GET or POST according to the JWT data. The GET or POST is two basic request commands of the http request, and any one of the two basic request commands can be selected to generate the resource access request. The resource access request comprises: the method comprises the steps of personal information access, personal position information access, historical order information access and other information access requests corresponding to information which can be presented in an interface corresponding to an APP or an applet, and all the information access requests are concentrated in resource access requests.
The resource access request of the client contains corresponding Token data. After the resource access request is generated, in order to ensure the confidentiality of the resource access request, the resource access request needs to be encrypted in advance, wherein the Token data is not encrypted during encryption so as to be called and searched in a later period.
And then, the client extracts the Token data in the resource access request to search whether matched Token data exists in a cookie storage bank of the client, if so, the matching is proved to be successful, a configuration file stored in the local of the client is directly called, signature information and an encryption key corresponding to the Token data are obtained from the configuration file, the resource access request is decoded by using the encryption key, and meanwhile, signature verification is carried out on the signature information and the Token data.
And after the client successfully decodes the resource access request and successfully verifies the signature, acquiring corresponding role authority information and sending the role authority information to the server.
Step F4, receiving the role authority information sent by the client to obtain corresponding display information, and sending the display information to the corresponding client.
Therefore, the server can acquire corresponding display information according to the role authority information. For example, some display contents required by the user targeted by the server and the contents stored in the database corresponding to the personal account are merged into the display information and sent to the client.
By the aid of the scheme, the confidentiality of the account information of the user can be guaranteed, the data transmission process can be accelerated, the accuracy of data transmission can be improved, and the efficiency is improved.
Another embodiment is as follows:
the information recognition neural network model can be used for processing owner information and/or vehicle information of a user side account or owner information and/or vehicle information of a resident user corresponding to a refueling station side account, determining a corresponding first petroleum type, determining corresponding target petroleum information according to the first petroleum type, and recommending the target petroleum information to the user side account or each resident user corresponding to the refueling station side account.
The vehicle owner information includes: name, age, gender, personal preferences, weight, etc., and the vehicle information includes: vehicle type, brand, displacement, vehicle model, color, etc.
The specific training process of the information recognition neural network model comprises the following steps:
step G1, obtaining a predetermined amount of information sample data, and adding a corresponding petroleum type label to each information sample data, wherein the information sample data comprises: personal sample information and/or vehicle sample information, the number of petroleum type tags is one or more.
Step G2, pre-constructing an information identification initial neural network, wherein the information identification initial neural network comprises: the system comprises an information identification input layer, N information identification hidden layers and an information identification output layer.
And G3, inputting information sample data from the information identification input layer, and processing the information sample data through N information identification hidden layers, wherein the first information identification hidden layer receives the data content output from the information identification input layer, and the rest information identification hidden layers receive the data content output after the last information identification hidden layer is processed.
And G4, the last information identification hidden layer outputs the processing result data to the information identification output layer so that the information identification output layer can determine the corresponding petroleum type according to the processing result data.
And G5, judging whether the output petroleum type is the same as the corresponding petroleum type label, if so, training next information sample data, and if not, adjusting parameters of each information identification hidden layer to enable the output petroleum type to be the same as the corresponding petroleum type label.
And G6, using the information recognition initial neural network after all information sample data are trained as an information recognition neural network model.
In the above scheme, the information identification input layer includes two types of input ports, specifically: the system comprises an owner information input port and a vehicle information input port, wherein owner information and/or vehicle information in information sample data are input from the corresponding input ports, and after data processing is carried out through an information identification input layer, character data are converted into code data so that an information identification hidden layer can further carry out information processing according to the data.
The number of the information identification hidden layers can be set according to the number of information types in personal sample information or vehicle sample information, one information identification hidden layer correspondingly processes one type of sample information, then a processing result is transmitted to the next information identification hidden layer to be processed, the next information identification hidden layer combines the processing result of the previous information identification hidden layer with the processing result of the sample information of the type corresponding to the information identification hidden layer and then transmits the combined result to the next information identification hidden layer, and the like is carried out until the last information identification hidden layer transmits the final processing result to the information identification output layer, and the information identification output layer converts the processing result into character information of the corresponding petroleum type and outputs the character information.
If the output petroleum type is the same as the corresponding petroleum type label, the next information sample data is directly processed without processing, if the output result is different, the output result of the information identification initial neural network is proved to be incorrect, the information identification initial neural network needs to be adjusted, and the parameters of each information identification hidden layer can be manually adjusted according to experience until the output result is the same as the petroleum type label. Or calculating a corresponding loss function according to the output petroleum type and petroleum type labels, automatically adjusting each information identification hidden layer according to the loss function, and then reprocessing the information sample data by using the adjusted information identification initial neural network until the output result is consistent with the petroleum type labels.
After all information sample data are trained, detecting the trained information recognition initial neural network by using a preset amount of detection sample data, judging the accuracy rate of a recognition result, if the accuracy rate exceeds a corresponding threshold value, proving that the trained information recognition initial neural network meets the standard and can be used as an information recognition neural network model, if the accuracy rate is less than the corresponding threshold value, reselecting the information sample data, and training the information recognition initial neural network again until the obtained accuracy rate of the information recognition initial neural network exceeds the corresponding threshold value.
And using the final information identification initial neural network as an information identification neural network model.
In another embodiment, the method comprises the following steps:
extracting corresponding historical petroleum order information of successful transaction from a user side, or extracting the historical petroleum order information of successful transaction of each resident user from a refueling station side; and if the historical petroleum order information is acquired by the refueling station terminal, dividing the historical petroleum order information according to each resident user, wherein each resident user corresponds to a group of historical petroleum order information of the resident user who successfully places the order at the refueling station.
Inputting the extracted historical petroleum order information into an order recognition neural network model, processing to obtain a corresponding second petroleum type, searching corresponding target petroleum information according to the second petroleum type, and recommending the target petroleum information to a corresponding user side or a user side corresponding to a resident user.
Or combining the first petroleum type and the second petroleum type to determine corresponding target petroleum information, and recommending the target petroleum information to a corresponding user side or a user side corresponding to a resident user.
The training process of the order recognition neural network model is as follows:
step I1, obtaining a preset amount of oil order sample data, and adding a corresponding oil type label for each oil order sample data, wherein the number of the oil type labels is one or more.
Step I2, pre-constructing an order identification initial neural network, wherein the order identification initial neural network comprises: the order recognition system comprises an order recognition input layer, M order recognition hidden layers and an order recognition output layer.
Step I3, inputting petroleum order sample data from an order identification input layer, and processing the petroleum order sample data through M order identification hidden layers, wherein the first order identification hidden layer receives data content output from the order identification input layer, and the rest of the order identification hidden layers are all data content output after the last order identification hidden layer is processed.
And step I4, the last order identification hidden layer outputs the processing result data to the order identification output layer, so that the order identification output layer determines the corresponding petroleum type according to the processing result data.
Step I5, judging whether the output petroleum type is the same as the corresponding petroleum type label, if so, training the sample data of the next petroleum order, if not, calculating an order loss function according to the output petroleum type and the corresponding petroleum type label, and adjusting the parameters of the order identification hidden layer according to the order loss function to ensure that the output petroleum type is the same as the corresponding petroleum type label.
Step I6, the order recognition initial neural network after the oil order sample data is completely trained is used as the order recognition neural network model.
In the above scheme, a plurality of input ports are included, and each input port can input order data. The number of input ports is greater than or equal to the maximum order data number. To ensure that multiple order data can be input simultaneously. The order identification input layer carries out data conversion processing on the order sample data and converts the order sample data into code data, so that the order identification hidden layer can carry out processing according to the code data.
The order sample data comprises a plurality of order data groups, each order data group is order data of the same user, each order data group can contain one or more order data, and the quantity of the input port takes the maximum order quantity in the order data groups as the set quantity of the input port. Or a predetermined value (e.g., 5) higher than the maximum order number as a set number of the input ports so as to ensure that the number of the input ports is in accordance with the demand in a practical situation.
The number of the order identification hidden layers is consistent with that of the input ports, each order is processed by one order data correspondingly by the hidden layers, then the processing result is transmitted to the next order identification hidden layer to be processed, the next order identification hidden layer combines the processing result of the previous order identification hidden layer with the processing result of the order data corresponding to the order identification hidden layer and then transmits the combined result to the next order identification hidden layer, and the like are repeated until the last order identification hidden layer transmits the final processing result to the order identification output layer, and the order identification output layer converts the processing result into the character information of the corresponding petroleum type and outputs the character information.
If the output petroleum type is the same as the corresponding petroleum type label, the next information sample data is directly processed without processing, if the output result of the order recognition initial neural network is different, the order recognition initial neural network is proved to be incorrect, the order recognition initial neural network needs to be adjusted, and the parameters of each order recognition hidden layer can be manually adjusted according to experience until the output result is the same as the petroleum type label. Or calculating a corresponding loss function according to the output petroleum type and petroleum type labels, automatically adjusting each order identification hidden layer according to the loss function, and then reprocessing the order sample data by using the adjusted order identification initial neural network until the output result is consistent with the petroleum type labels.
After all the order sample data are trained, detecting the trained order identification initial neural network by using a predetermined amount of detection sample data, judging the accuracy rate of the identification result, if the accuracy rate exceeds a corresponding threshold value, proving that the trained order identification initial neural network meets the standard and can be used as an order identification neural network model, if the accuracy rate is less than the corresponding threshold value, reselecting the information sample data, and training the order identification initial neural network again until the obtained accuracy rate of the order identification initial neural network exceeds the corresponding threshold value.
And using the final order identification initial neural network as an order identification neural network model.
In a specific embodiment, if the petroleum operation data is the information of ordering the user by refueling sent from the client, the specific processing procedure of the processing server in step 103 includes: the server is also capable of performing:
and step H1, receiving the order information sent by the client, wherein the order information comprises the target petroleum commodity, the position information of the client, the target gas station and the refueling time period.
Wherein, if user's vehicle need refuel, can trigger APP or the corresponding refuel button or the corresponding service of refueling of pronunciation trigger in the applet on the client, and then form the user and refuel the information of placing an order.
And step H2, extracting the position information of the client in the information of ordering the user, searching the position information of the target gas station in the map, and calculating the time consumed by the client to reach the target gas station.
The method comprises the steps of marking in a map according to the position information of a client and the position information of a target gas station, calculating a route from the position of the client to the position of the target gas station, and further calculating the time consumed by the vehicle to travel according to the route and the average time of each vehicle passing through the route.
And step H3, if the current time plus the bus trip consuming time is less than or equal to the latest time point of the refueling time period, acquiring whether a target petroleum commodity of the target refueling station has a residual oil outlet in the refueling time period, if so, sending the refueling order information of the user to a refueling station end of the target refueling station for confirmation and receiving, and simultaneously generating a confirmation receiving instruction to send to the client, otherwise, refusing to receive the refueling order information of the user, generating a refusing receiving instruction to send to the client.
And if the calculated time consumption of the vehicle journey and the latest time point when the current time is less than or equal to the refueling time period are added, the fact that the user can arrive at a refueling station within the refueling time period is proved to refuel. In this case, if the order quantity of the corresponding target petroleum commodity of the gas station in the refueling time period has reached the maximum order quantity and no oil outlet remains, it is proved that the refueling time period cannot be performed even if the user arrives at the gas station. And correspondingly generating a receiving refusing instruction, wherein the receiving refusing instruction comprises other available order time periods of the target petroleum commodity. Therefore, after the client receives the final receiving instruction, the user can reselect other time periods for refueling according to the actual situation of the gas station. Or the user can select other gas stations to refuel, and the selection is determined according to the actual needs of the user.
And step H4, if the current time plus the bus trip consumption time is larger than the latest time point of the refueling time period, refusing to receive the refueling order information of the user, generating a re-confirmation refueling time period instruction and sending the re-confirmation refueling time period instruction to the client.
If the current time plus the vehicle journey consumed time is larger than the latest time point of the refueling time period, the fact that the user cannot arrive at the refueling station in the refueling time period is proved, the server automatically refuses to receive the refueling order placing information, obtains other time periods capable of receiving orders of the target petroleum commodity of the refueling station, adds the time periods into the refueling time period reconfirming instruction, and sends the instruction to the client side so that the user can reselect other time periods to refuel according to the actual situation of the refueling station. Or the user can select other gas stations to refuel, and the selection is determined according to the actual needs of the user.
Through the scheme, the server can process the refueling ordering information of the user in advance, and timely informs the user of the refueling ordering information which cannot be completed at all, so that the user can change the refueling ordering in time, and the condition that the refueling cannot be carried out due to the fact that the refueling station cannot be reached in time is reduced.
In a specific embodiment, if the petroleum operation data is a command sent by the client to enter the gas station, the processing server can further execute:
and step J1, receiving the command of entering the gas station from the client, and acquiring the position information of the client.
In the step, the user wants to select a common gas station as a resident gas station, the user can correspondingly form a resident gas station command by triggering a resident gas station button on the client, and the client can send the resident gas station command to the server. And after receiving the position information, the server acquires the position information of the client, and further searches the corresponding gas station according to the position of the client.
The location information of the client may be the current location information of the client, or the location information of a place where the user has frequently set in advance.
And step J2, determining at least one gas station with the distance less than or equal to the distance threshold according to the position information of the client, and sending the at least one gas station to the client so that the client can select from the at least one gas station.
And step J3, receiving the selected target stop filling station sent by the client, integrating the target stop filling station and stop filling station commands, and sending the integrated information to the filling station end corresponding to the target stop filling station so that the filling station end establishes stop connection with the client through the server.
In the step, after the integrated information is sent to the fueling station end corresponding to the target entry fueling station, and the fueling station end receives the integrated information, entry connection can be established at the client, so that the fueling station end can directly send corresponding discount information or preferential information to the client in time.
In addition, after the filling station end establishes the parking connection with the client, a successful parking instruction is sent to the server, and the server stores the parked filling station into the parking cache library corresponding to the client. And meanwhile, storing the relevant information of the client into a resident user cache library corresponding to the refueling station.
The various gas stations can also adopt discount or discount for each resident user, and specific discount or discount measures are selected according to the actual situation of each gas station. The user can enter the homepage of the gas station through the APP or the applet on the client side, and the corresponding preferential information is checked in the homepage.
One or more filling stations selected by the user can be selected, so that if the corresponding filling station publishes new petroleum information, the new petroleum information can be displayed in the information recommendation column of the corresponding display screen.
The resident gas station can also be displayed in a corresponding resident gas station column of the user client, the display sequence can be arranged in sequence according to the distance from the current position of the user, the selected resident time, the access amount, the order amount and the like, and the user can select the corresponding arrangement mode according to the actual requirement.
Through the scheme, the function of selecting the oil filling station to park can be provided for the user through the server, so that the user can check some petroleum information and some preferential information corresponding to the oil filling station to be published in time, and convenience is provided for the user.
In addition, as a supplement to the solution of this embodiment, if the petroleum operation data is an invoice request instruction sent by the client, the specific processing procedure of the processing server in step 103 includes:
and step K1, receiving an invoice request instruction sent by the client.
And step K2, searching the corresponding petroleum order information and the invoicing record of the corresponding petroleum order information from the storage database of the corresponding gas station account according to the invoice request instruction.
And step K3, if the billing record is empty, acquiring the amount data of the petroleum order information from the corresponding storage database of the gas station account, extracting the billing account information in the invoice request instruction, correspondingly generating electronic invoice information, sending the electronic invoice information to the client, and if the billing record has the corresponding electronic invoice information, generating a billing rejection instruction and sending the billing rejection instruction to the client.
In the above scheme, if the user wants to invoice, the user can select to send an invoice request instruction to the refueling station end through the APP or applet of the user end, and issue a corresponding electronic invoice. The method specifically comprises the following steps:
the method comprises the steps that a user triggers an APP or an invoice issuing key in the petroleum commodity after transaction in an applet succeeds through a user side, an invoice request instruction is formed and sent to a server, wherein the invoice request instruction comprises information corresponding to a gas station, the server searches the corresponding gas station according to the information of the gas station, whether the corresponding transaction exists in a storage database of an account number of the corresponding gas station and after the corresponding transaction succeeds is determined, whether the transaction has issued invoice information or not is checked, if not, corresponding invoice information is issued according to the transaction amount and the invoice issuing information carried in the corresponding invoice request instruction, the invoice information is sent to the client side and displayed.
Through the technical scheme, the intelligent invoice issuing function and the function of counting various data information are provided for the user, so that the user can use the invoice more conveniently.
Based on the embodiment corresponding to fig. 1, the present embodiment proposes a network-based oil operation data processing apparatus, as shown in fig. 2, including:
the receiving module 21 is configured to receive petroleum operation data information sent by a client through the internet or a virtual private network, where the client is a user side and/or a fueling station side;
the inspection module 22 is used for carrying out safety inspection on the petroleum operation data, intercepting the petroleum operation data if the petroleum operation data contains dangerous information, and releasing the petroleum operation data if the petroleum operation data does not contain dangerous information;
the processing module 23 is used for transmitting the released petroleum operation data to the processing server through the NAT gateway and the router for processing;
and the storage module 24 is configured to program the data processed by the processing server by using a structured query language and store the data in the database server.
In a specific embodiment, if the oil operation data is issued oil information sent from the fueling station, the processing module 23 is specifically configured to:
the released oil product information is transmitted to a processing server through an NAT gateway and a router; the processing server inputs the published oil product information into an oil product type identification model for processing, and outputs the published oil product type corresponding to the published oil product information, wherein the oil product type identification model is obtained by training a neural network by using sample oil product information which is marked with oil product types in advance; the processing server searches a corresponding target auditing standard in the memory according to the issued oil product category, wherein the auditing standard corresponding to each oil product category is stored in the memory in advance; the processing server checks various parameters of the issued oil product information according to the target auditing standard, and if the checking is successful, the issued oil product information is used as processed data;
then, the apparatus further comprises:
and the sending module is used for pushing the programmed data stored in the database server to an account platform corresponding to the refueling station end for issuing.
In a specific embodiment, the processing module 23 is further specifically configured to:
obtaining sample oil information of a preset quantity, and adding a corresponding oil type label to each sample oil information, wherein each sample oil information comprises a plurality of oil information data; the method comprises the steps of constructing an oil product identification initial neural network with an oil product identification input layer, N oil product identification hidden layers and an oil product identification output layer in advance, wherein the construction number N of the oil product identification hidden layers is more than or equal to the maximum value X of the number of oil product information data in sample oil product information; inputting sample oil product information from an oil product identification input layer, and processing the sample oil product information through N oil product identification hidden layers, wherein the first oil product identification hidden layer receives data content output from the oil product identification input layer, and the rest oil product identification hidden layers receive data content output after the previous oil product identification hidden layer is processed; the last oil product identification hidden layer outputs the processing result data to the oil product identification output layer, and the oil product identification output layer determines the corresponding output oil product type according to the processing result data; judging whether the output oil type is the same as the corresponding oil type label, if so, training the next sample oil information, and if not, adjusting the parameters of each oil identification hidden layer to ensure that the output oil type is the same as the corresponding oil type label; and taking the oil product identification initial neural network after the sample oil product information is completely trained as an oil product identification model, and storing the oil product identification model into a processing server.
In a specific embodiment, if the petroleum operation data is information to be released of petroleum knowledge sent from the fueling station side and/or the user side, the processing module 23 is further specifically configured to:
transmitting the released petroleum knowledge to-be-released information to a processing server through an NAT gateway and a router; the processing server inputs the information to be published of the petroleum knowledge into a knowledge category identification model for processing, and outputs the knowledge category to be published corresponding to the information to be published of the petroleum knowledge, wherein the knowledge category identification model is obtained by training a neural network by using sample petroleum knowledge information which is marked with the knowledge category in advance; and the processing server marks the information to be published of the petroleum knowledge by using the category of the knowledge to be published, and takes the marked information to be published of the petroleum knowledge as processed data.
And the sending module is further used for pushing the programmed data stored in the database server to an account platform corresponding to the refueling station end and/or the user end for issuing.
In a specific embodiment, the processing module 23 is further specifically configured to:
acquiring a preset number of sample petroleum knowledge information, and adding a corresponding knowledge category label to each sample petroleum knowledge information; the method comprises the steps that a knowledge identification initial neural network with a knowledge identification input layer, M knowledge identification hidden layers and a knowledge identification output layer is constructed in advance, wherein each knowledge identification hidden layer correspondingly identifies the coincidence probability of a knowledge category, and the construction number M of the knowledge identification hidden layers is greater than or equal to the maximum value Q of the category number of the knowledge categories in sample petroleum knowledge information; inputting sample petroleum knowledge information from a knowledge identification input layer, and extracting keywords from the sample petroleum knowledge information by the knowledge identification input layer; the knowledge identification input layer respectively inputs the extracted keywords into each knowledge identification hidden layer for processing, and each knowledge identification hidden layer correspondingly outputs the probability P belonging to the corresponding knowledge category1，P2，……，PMAnd respectively sending the data to a knowledge identification output layer; the knowledge identification output layer screens out the knowledge category corresponding to the maximum value of the probability of the knowledge category as an output knowledge category, judges whether the output knowledge category is the same as the corresponding knowledge category label or not, trains the next sample petroleum knowledge information if the output knowledge category is the same as the corresponding knowledge category label, otherwise trains the knowledge categoryAdjusting parameters of the knowledge identification hidden layer corresponding to the identification labels to enable the probability of the processed and output knowledge type to be 100%, and then training the petroleum knowledge information of the next sample; and (3) taking the knowledge identification initial neural network after the sample petroleum knowledge information is completely trained as a knowledge category identification model, and storing the knowledge category identification model into a processing server.
In an embodiment, if the oil operation data information is order data of a successful transaction of the fueling station end within a set time period, the processing module 23 is further configured to:
transmitting the order data of successful released transaction to a processing server through an NAT gateway and a router; the processing server calculates the cost amount of each successful transaction order data according to the petroleum type and the petroleum amount in the successful transaction order data; calculating corresponding profit amount according to the cost amount and the transaction amount of each successful order data, and establishing a coordinate system by taking the profit amount as a vertical axis and corresponding time as a horizontal axis; the processing server analyzes the coordinate system, determines a corresponding operation state, and takes the operation state as processed data, specifically as follows: and if the coordinate system is an overall ascending trend, determining that the account corresponding to the refueling station end belongs to ascending type operation, if the coordinate system is an upward and downward fluctuating trend, determining that the account corresponding to the refueling station end belongs to stable type operation, and if the coordinate system is an overall descending trend, determining that the account corresponding to the refueling station end belongs to descending type operation.
And the sending module is also used for pushing the programmed data stored in the database server to the refueling station end for display.
In an embodiment, if the oil operation data is an oil inspection instruction sent from the user terminal and/or the fueling station terminal, the processing module 23 is further configured to:
transmitting the released oil product inspection instruction to a processing server through an NAT gateway and a router, wherein the oil product inspection instruction contains the petroleum type; the processing server extracts the oil type in the oil product inspection instruction, and at least one inspection station to be determined with oil type inspection qualification is searched from the map; the processing server acquires the position information of the user side and/or the refueling station side, and searches for a determined inspection station belonging to the same city level as the position information from at least one inspection station to be determined; if a plurality of the found determined inspection stations are arranged, the inspection stations are arranged according to the sequence of the distance from the position information to the user side and/or the refueling station side so that the user side and/or the refueling station side can select a target inspection station from the plurality of the determined inspection stations; the processing server receives a target inspection station and delivery time sent by the released user side and/or the refueling station side through the Internet or a virtual private network, acquires whether delivery service corresponding to the petroleum type of the target inspection station in the delivery time is saturated or not, generates a delivery refusing instruction to be sent to the user side and/or the refueling station side if the delivery service is saturated, so that the user side and/or the refueling station side can determine the target inspection station again, packages the oil product inspection instruction and the delivery time if the delivery service is not saturated, and takes the packaged data as processed data.
The sending module is further configured to send the programmed data stored in the database server to the target inspection station.
Based on the above embodiments of the method shown in fig. 1 and the apparatus shown in fig. 2, in order to achieve the above object, an electronic device is further provided in the embodiments of the present application, as shown in fig. 3, including a memory 32 and a processor 31, where the memory 32 and the processor 31 are both disposed on a bus 33, the memory 32 stores a computer program, and the processor 31 implements the network-based oil operation data processing method shown in fig. 1 when executing the computer program.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile memory (which may be a CD-ROM, a usb disk, a removable hard disk, or the like), and includes several instructions for enabling an electronic device (which may be a personal computer, a server, or a network device, or the like) to execute the method according to the implementation scenarios of the present application.
Optionally, the device may also be connected to a user interface, a network interface, a camera, Radio Frequency (RF) circuitry, sensors, audio circuitry, a WI-FI module, and so forth. The user interface may include a Display screen (Display), an input unit such as a keypad (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., a bluetooth interface, WI-FI interface), etc.
It will be understood by those skilled in the art that the structure of an electronic device provided in the present embodiment does not constitute a limitation of the physical device, and may include more or less components, or some components in combination, or a different arrangement of components.
Based on the embodiments of the method shown in fig. 1 and the apparatus shown in fig. 2, correspondingly, the present application also provides a storage medium, on which a computer program is stored, which when executed by a processor implements the network-based oil operation data processing method shown in fig. 1.
The storage medium may further include an operating system and a network communication module. An operating system is a program that manages the hardware and software resources of an electronic device, supporting the operation of information handling programs, as well as other software and/or programs. The network communication module is used for realizing communication among components in the storage medium and communication with other hardware and software in the electronic equipment.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present application can be implemented by software plus a necessary general hardware platform, and can also be implemented by hardware.
By applying the technical scheme of the application, the petroleum operation data sent by the user side and/or the refueling station side through the Internet or the virtual private network is subjected to security check, no dangerous information is determined, the petroleum operation data is transmitted to the processing server through the NAT gateway and the router to be further processed according to the specific content of the petroleum operation data, and the processing result is programmed by using the structured query language and is stored in the database server. Therefore, the safety of the petroleum operation data can be guaranteed, and meanwhile, the processing speed of the petroleum operation data can be increased.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above application serial numbers are for description purposes only and do not represent the superiority or inferiority of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.
Claims (10)
1. A network-based petroleum operation data processing method is characterized by comprising the following steps:
receiving petroleum operation data information sent by a client through the Internet or a virtual private network, wherein the client is a user side and/or a refueling station side;
carrying out safety inspection on the petroleum operation data, intercepting the petroleum operation data if the petroleum operation data contains dangerous information, and otherwise, releasing the petroleum operation data;
transmitting the released petroleum operation data to a processing server through an NAT gateway and a router for processing;
and programming the data processed by the processing server by using a structured query language and storing the data into the database server.
2. The network-based oil operation data processing method according to claim 1, wherein if the oil operation data is issued oil information from a fueling station, the passing oil operation data is transmitted to a processing server through an NAT gateway and a router for processing, specifically comprising:
transmitting the released oil product information to the processing server through an NAT gateway and a router;
the processing server inputs the issued oil product information into an oil product type identification model for processing, and outputs the issued oil product type corresponding to the issued oil product information, wherein the oil product type identification model is obtained by training a neural network by using sample oil product information which is marked with oil product types in advance;
the processing server searches a corresponding target auditing standard in a memory according to the issued oil product category, wherein the auditing standard corresponding to each oil product category is stored in the memory in advance;
the processing server checks various parameters of the issued oil product information according to the target auditing standard, and if the checking is successful, the issued oil product information is used as processed data;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and pushing the programmed data stored in the database server to an account platform corresponding to the refueling station terminal for release.
3. The network-based oil operation data processing method according to claim 2, wherein before the processing server inputs the published oil product information into an oil product type identification model for processing and outputs the published oil product type corresponding to the published oil product information, the method specifically comprises:
obtaining sample oil information of a preset quantity, and adding a corresponding oil type label to each sample oil information, wherein each sample oil information comprises a plurality of oil information data;
an oil product identification initial neural network with an oil product identification input layer, N oil product identification hidden layers and an oil product identification output layer is constructed in advance, wherein the construction number N of the oil product identification hidden layers is more than or equal to the maximum value X of the number of oil product information data in the sample oil product information;
inputting the sample oil product information from an oil product identification input layer, and processing the sample oil product information through the N oil product identification hidden layers, wherein the first oil product identification hidden layer receives data content output from the oil product identification input layer, and the rest oil product identification hidden layers receive data content output after the previous oil product identification hidden layer is processed;
the last oil product identification hidden layer outputs the processing result data to the oil product identification output layer so that the oil product identification output layer can determine the corresponding output oil product type according to the processing result data;
judging whether the output oil type is the same as the corresponding oil type label, if so, training the next sample oil information, and if not, adjusting the parameters of each oil identification hidden layer to ensure that the output oil type is the same as the corresponding oil type label;
and taking the oil product identification initial neural network after the sample oil product information is completely trained as an oil product identification model, and storing the oil product identification model into a processing server.
4. The network-based oil operation data processing method according to claim 1, wherein if the oil operation data is information to be released of oil knowledge sent from a fueling station side and/or a user side, the released oil operation data is transmitted to a processing server through an NAT gateway and a router for processing, specifically comprising:
transmitting the released petroleum knowledge to-be-released information to the processing server through the NAT gateway and the router;
the processing server inputs the information to be published of the petroleum knowledge into a knowledge category identification model for processing, and outputs the knowledge category to be published corresponding to the information to be published of the petroleum knowledge, wherein the knowledge category identification model is obtained by training a neural network by using sample petroleum knowledge information which is labeled with the knowledge category in advance;
the processing server marks the information to be published of the petroleum knowledge by using the type of the knowledge to be published, and takes the marked information to be published of the petroleum knowledge as processed data;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and pushing the programmed data stored in the database server to an account platform corresponding to the refueling station terminal and/or the user terminal for issuing.
5. The network-based oil operation data processing method according to claim 4, wherein before the processing server inputs the information to be published of the oil knowledge into the knowledge class identification model for processing and outputs the knowledge class to be published corresponding to the information to be published of the oil knowledge, the method specifically comprises:
acquiring a preset number of sample petroleum knowledge information, and adding a corresponding knowledge category label to each sample petroleum knowledge information;
pre-constructing a knowledge identification initial neural network with a knowledge identification input layer, M knowledge identification hidden layers and a knowledge identification output layer, wherein each knowledge identification hidden layer correspondingly identifies the coincidence probability of a knowledge category, and the construction number M of the knowledge identification hidden layers is more than or equal to the maximum value Q of the category number of the knowledge categories in the sample petroleum knowledge information;
inputting the sample petroleum knowledge information from a knowledge identification input layer, and extracting key words from the sample petroleum knowledge information by the knowledge identification input layer;
the knowledge identification input layer respectively inputs the extracted keywords into each knowledge identification hidden layer for processing, and each knowledge identification hidden layer correspondingly outputs the probability P belonging to the corresponding knowledge category1，P2，……，PMAnd respectively sending the data to the knowledge identification output layer;
the knowledge identification output layer screens out the knowledge category corresponding to the maximum value of the probability of the knowledge category as an output knowledge category, judges whether the output knowledge category is the same as the corresponding knowledge category label or not, trains the next sample petroleum knowledge information if the output knowledge category is the same as the corresponding knowledge category label, otherwise, trains the next sample petroleum knowledge information after adjusting the parameters of the knowledge identification hidden layer corresponding to the knowledge category label to make the probability of the processed output knowledge category 100%;
and taking the knowledge identification initial neural network after the sample petroleum knowledge information is completely trained as a knowledge category identification model, and storing the knowledge category identification model into a processing server.
6. The network-based oil operation data processing method according to claim 1, wherein if the oil operation data information is order data of successful transaction in a set time period at the fueling station, the passing oil operation data is transmitted to the processing server through the NAT gateway and the router for processing, specifically comprising:
transmitting the order data of successful released transaction to the processing server through the NAT gateway and the router;
the processing server calculates the cost amount of each successful transaction order data according to the petroleum type and the petroleum amount in the successful transaction order data; calculating corresponding profit amount according to the cost amount and the transaction amount of each successful order data, and establishing a coordinate system by taking the profit amount as a vertical axis and corresponding time as a horizontal axis;
the processing server analyzes the coordinate system, determines a corresponding operation state, and takes the operation state as processed data, specifically: if the coordinate system is an integral ascending trend, determining that the account corresponding to the refueling station end belongs to ascending operation, if the coordinate system is an up-and-down fluctuation trend, determining that the account corresponding to the refueling station end belongs to stable operation, and if the coordinate system is an integral descending trend, determining that the account corresponding to the refueling station end belongs to descending operation;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and pushing the programmed data stored in the database server to the refueling station end for display.
7. The network-based oil operation data processing method according to claim 1, wherein if the oil operation data is an oil product inspection instruction sent from a user terminal and/or an oil filling station terminal, the passing oil operation data is transmitted to a processing server through an NAT gateway and a router for processing, specifically comprising:
transmitting the released oil product inspection instruction to the processing server through an NAT gateway and a router, wherein the oil product inspection instruction contains the petroleum type;
the processing server extracts the oil type in the oil product inspection instruction, and at least one inspection station to be determined with the oil type inspection qualification is searched from a map;
the processing server acquires the position information of the user side and/or the refueling station side, and searches for a determined inspection station belonging to the same city level as the position information from at least one inspection station to be determined; if a plurality of the found determined inspection stations exist, arranging the inspection stations according to the sequence of the distance from the position information to the far position, and then sending the inspection stations to the user side and/or the refueling station side so that the user side and/or the refueling station side can select a target inspection station from the plurality of the determined inspection stations;
the processing server receives a target inspection station and delivery time sent by the released user side and/or the released refueling station side through the Internet or a virtual private network, acquires whether delivery service corresponding to the petroleum type of the target inspection station in the delivery time is saturated or not, generates a delivery refusal instruction to be sent to the user side and/or the refueling station side if the delivery service is saturated, so that the user side and/or the refueling station side can determine the target inspection station again, packages the oil product inspection instruction and the delivery time if the delivery service is not saturated, and takes the packaged data as processed data;
after the programming the data processed by the processing server by using the structured query language and storing the data in the database server, the method further comprises:
and sending the programmed data stored in the database server to the target inspection station.
8. A network-based oil-run data processing apparatus, comprising:
the system comprises a receiving module, a data processing module and a data processing module, wherein the receiving module is used for receiving petroleum operation data information sent by a client through the Internet or a virtual private network, and the client is a user side and/or a refueling station side;
the inspection module is used for carrying out safety inspection on the petroleum operation data, intercepting the petroleum operation data if the petroleum operation data contains dangerous information, and releasing the petroleum operation data if the petroleum operation data does not contain dangerous information;
the processing module is used for transmitting the released petroleum operation data to the processing server through the NAT gateway and the router for processing;
and the storage module is used for programming the data processed by the processing server by using a structured query language and storing the data into the database server.
9. An electronic device comprising a memory and a processor, the memory storing a computer program, wherein the processor when executing the computer program implements the steps of the network-based oil operational data processing method according to any one of claims 1 to 7.
10. A storage medium having stored thereon a computer program, characterized in that the computer program, when being executed by a processor, realizes the steps of the network-based oil operational data processing method according to any one of claims 1 to 7.
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