CN117076895A - Intelligent analysis method and system for energy supply information - Google Patents
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Abstract
The invention provides an intelligent analysis method and system for energy supply information, comprising the following steps: when an energy supply station is started, acquiring actual energy supply information when the energy supply station is started, inputting the actual energy supply information into an energy network model, predicting corresponding energy parameter adjustment values, and predicting corresponding energy mode adjustment values; respectively taking the energy parameter adjustment values and the energy mode adjustment values as input parameters to a preset energy adjustment script, and judging whether the corresponding values can be output or not; and if the corresponding value can be output, adjusting the supply parameter of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value. According to the invention, the actual energy supply information is predicted through the trained network model to obtain the energy parameter adjustment value and the energy mode adjustment value, so that the supply parameters are adjusted, the dependence on manual experience and static rules is avoided, and the analysis and prediction capability of real-time data is improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent analysis method and system for energy supply information.
Background
With the continuous growth of global energy demands and the limitation of energy resources, it is important to manage energy supply information of energy supply stations.
How to efficiently manage and adjust the energy parameters and modes of the energy supply station becomes critical. At present, the traditional energy supply station management method often depends on manual experience and static rules, and lacks the capability of analyzing and predicting real-time data. Further, when managing energy replenishment information, a large amount of data is involved, and data management and data security are also a major problem currently faced.
Disclosure of Invention
The invention mainly aims to provide an intelligent analysis method and system for energy supply information, and aims to overcome the defect that the management mode of the current energy supply station depends on manual experience and static rules and lacks of analysis and prediction capability for real-time data.
In order to achieve the above object, the present invention provides an intelligent analysis method for energy supply information, comprising the following steps:
when an energy supply station is started, acquiring actual energy supply information when the energy supply station is started, and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model;
Based on the energy parameter adjustment model, predicting corresponding energy parameter adjustment values according to actual energy supply information of the energy supply station; the energy parameter adjusting value is used for adjusting energy parameters of energy supply;
based on the energy mode adjustment model, predicting a corresponding energy mode adjustment value according to actual energy supply information of the energy supply station; the energy mode adjusting value is used for adjusting an energy mode of energy supply;
respectively taking the energy parameter adjustment value and the energy mode adjustment value as input parameters to a preset energy adjustment script, and judging whether the corresponding values can be output or not; the preset energy adjustment script comprises detection logic for detecting whether an energy parameter adjustment value and an energy mode adjustment value meet standards or not;
and if the corresponding value can be output, adjusting the supply parameter of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value.
Further, the training process of the energy mode adjustment model includes:
acquiring energy supply training data; wherein the energy supply training data comprises a plurality of training information;
for each energy supply training data, after hiding any training information in the energy supply training data at random each time, inputting the energy supply training data into an initial energy mode adjustment model for prediction to obtain a corresponding energy mode adjustment prediction result;
And adjusting model parameters of the initial energy mode adjustment model so that training data are supplied for each energy source, and after one piece of training information is hidden, the corresponding energy mode adjustment prediction results are the same.
Further, if the corresponding value can be output, the step of adjusting the supply parameter of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value includes:
adding the actual energy supply information into a preset layer to obtain an actual energy supply picture;
dividing the actual energy supply picture into a first picture, a second picture and a third picture;
encrypting the first picture, the second picture and the third picture according to a preset encryption rule; the first picture, the second picture and the third picture are different in encryption mode;
and storing the encrypted first picture, the encrypted second picture and the encrypted third picture into the same folder of the database.
Further, the step of encrypting the first picture, the second picture and the third picture according to a preset encryption rule includes:
acquiring picture parameters of the first picture; the picture parameters comprise picture data quantity, height and width, wherein the picture data quantity, the width and the height are all integers;
Converting a preset coding table based on the picture data amount to obtain a conversion coding table; the conversion coding table comprises two columns, wherein one column is a number, and the other column is a character mapped with the number one by one;
coding the width and the height based on the conversion coding table respectively to obtain a width code and a height code; combining the width code and the height code to obtain a first encryption password; encrypting the first picture based on the first encryption password;
acquiring data information stored in a designated position of the first picture, and encoding the data information by adopting the conversion encoding table to obtain data information encoding; acquiring the creation time of the second picture; wherein the creation time includes a year;
encoding the creation time based on the conversion encoding table to obtain a time code; combining the data information code with the time code to obtain a second encryption password; encrypting the second picture based on the second encryption password;
carrying out hash operation on the encrypted second picture to obtain a corresponding hash value; based on a preset character selection rule, selecting corresponding characters from the hash value to be combined, and obtaining a hash character combination;
Decoding the hash character combination based on the conversion coding table to obtain a corresponding decoding number; acquiring the resolution of the third picture, and encoding numbers in the resolution of the third picture into corresponding resolution codes based on the conversion encoding table; and combining the decoded number with the resolution code to obtain a third encryption password to encrypt the third picture.
Further, the step of converting the preset encoding table based on the picture data amount to obtain a converted encoding table includes:
acquiring a plurality of single digits included in the picture data amount, and adding the single digits to obtain a first digit;
acquiring a preset encoding table, searching a first character corresponding to a first number in the encoding table, and detecting whether the character in the encoding table before the first character is larger than n;
if the number is larger than the first character, moving the first character and all the characters after the first character forward by n bits together, and sequentially translating n characters before the first character to the tail of the coding table to fill the complete coding table to obtain the conversion coding table;
if not, the first character and all characters before the first character are jointly moved backwards by n bits, and n characters after the first character are sequentially translated to the head of the coding table so as to fill the complete coding table, and the conversion coding table is obtained.
Further, the step of converting the preset encoding table based on the picture data amount to obtain a converted encoding table includes:
acquiring a preset encoding table, and encoding the picture data amount based on the encoding table to obtain data encoding characters; wherein the data encoding characters comprise a plurality of characters;
sequentially searching the data coding characters in the coding table and removing the data coding characters; dividing the data coding character into a first coding character and a second coding character according to a preset rule;
and inserting the first coding character into the head part of the coding table, inserting the second coding character into the tail part of the coding table, and translating other characters in the coding table to fill the complete coding table, so as to obtain the conversion coding table.
The invention also provides an intelligent analysis system of the energy supply information, which comprises:
the energy supply system comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring actual energy supply information when the energy supply station is started and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model;
The first prediction unit is used for predicting corresponding energy parameter adjustment values according to the actual energy supply information of the energy supply station based on the energy parameter adjustment model; the energy parameter adjusting value is used for adjusting energy parameters of energy supply;
the second prediction unit is used for predicting a corresponding energy mode adjustment value according to the actual energy supply information of the energy supply station based on the energy mode adjustment model; the energy mode adjusting value is used for adjusting an energy mode of energy supply;
the judging unit is used for respectively inputting the energy parameter adjustment value and the energy mode adjustment value into a preset energy adjustment script as input parameters and judging whether the corresponding values can be output or not; the preset energy adjustment script comprises detection logic for detecting whether an energy parameter adjustment value and an energy mode adjustment value meet standards or not;
and the adjusting unit is used for adjusting the supply parameters of the energy supply station based on the energy parameter adjusting value and the energy mode adjusting value if the corresponding values can be output.
The invention also provides a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of any of the methods described above when the computer program is executed.
The invention also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method of any of the preceding claims.
The invention provides an intelligent analysis method and system for energy supply information, comprising the following steps: when an energy supply station is started, acquiring actual energy supply information when the energy supply station is started, and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model; based on the energy parameter adjustment model, predicting corresponding energy parameter adjustment values according to actual energy supply information of the energy supply station; the energy parameter adjusting value is used for adjusting energy parameters of energy supply; based on the energy mode adjustment model, predicting a corresponding energy mode adjustment value according to actual energy supply information of the energy supply station; the energy mode adjusting value is used for adjusting an energy mode of energy supply; respectively taking the energy parameter adjustment value and the energy mode adjustment value as input parameters to a preset energy adjustment script, and judging whether the corresponding values can be output or not; the preset energy adjustment script comprises detection logic for detecting whether an energy parameter adjustment value and an energy mode adjustment value meet standards or not; and if the corresponding value can be output, adjusting the supply parameter of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value. According to the invention, the actual energy supply information is predicted through the trained network model to obtain the energy parameter adjustment value and the energy mode adjustment value, so that the supply parameters are adjusted without depending on artificial experience and static rules, and the analysis and prediction capability of real-time data is improved.
Drawings
FIG. 1 is a schematic diagram showing steps of an intelligent analysis method for energy supply information according to an embodiment of the present invention;
FIG. 2 is a block diagram of an intelligent analysis device for energy supply information according to an embodiment of the present invention;
fig. 3 is a block diagram schematically illustrating a structure of a computer device according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, in one embodiment of the present invention, an intelligent analysis method for energy supply information is provided, including the following steps:
step S1, when an energy supply station is started, acquiring actual energy supply information when the energy supply station is started, and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model;
Step S2, based on the energy parameter adjustment model, predicting corresponding energy parameter adjustment values according to actual energy supply information of the energy supply station; the energy parameter adjusting value is used for adjusting energy parameters of energy supply;
step S3, based on the energy mode adjustment model, predicting a corresponding energy mode adjustment value according to the actual energy supply information of the energy supply station; the energy mode adjusting value is used for adjusting an energy mode of energy supply;
step S4, respectively taking the energy parameter adjustment value and the energy mode adjustment value as input parameters to a preset energy adjustment script, and judging whether the corresponding values can be output or not; the preset energy adjustment script comprises detection logic for detecting whether an energy parameter adjustment value and an energy mode adjustment value meet standards or not;
and step S5, if the corresponding value can be output, adjusting the supply parameter of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value.
In this embodiment, the above scheme is applied to analysis of energy supply information of an energy supply station, so that supply parameters are adjusted from two different dimensions of an energy parameter adjustment value and an energy mode adjustment value, and the analysis and prediction capabilities of real-time data are improved without relying on manual experience and static rules.
When the energy supply station is started, the monitoring system obtains the actual energy supply information, and inputs the actual energy supply information into the energy network model for analysis and prediction, as described in step S1. The actual energy replenishment information is actual replenishment information acquired by the energy replenishment station at the time of startup. The information includes the input energy type of the energy supply station, the current, voltage and power of the supply station, the operation mode, the operation state and the operation time of the supply station, and the like. By collecting and monitoring such actual replenishment information, the energy network model may analyze and predict the performance and demand of the energy replenishment station. The energy network model is a comprehensive model and comprises an energy parameter adjustment model and an energy mode adjustment model.
The function of the energy parameter adjustment model is to predict the corresponding energy parameter adjustment value according to the actual energy supply information of the energy supply station. The energy parameter adjustment values described above may be used to optimize parameters during the energy replenishment process, such as the energy capacity of the replenishment station, the energy delivery rate, or finer current, voltage control. The energy parameter adjustment model can predict the optimal energy parameter adjustment value by analyzing the actual energy supply information and the historical data so as to realize more efficient and more stable energy supply.
The energy mode adjustment model predicts a corresponding energy mode adjustment value according to the actual energy supply information. The energy mode adjustment value is used for adjusting the mode or strategy of energy supply so as to adapt to different application scenes and requirements. For example, for a photovoltaic replenishment station, the energy mode adjustment model may select an optimal photovoltaic power generation mode according to weather prediction, grid load conditions, and the like, to maximize energy utilization efficiency and economy.
As described in step S2 above, training of the energy parameter adjustment model relies on a large amount of measured and historical data. By analyzing the factors such as the running state, running time, load condition and the like of the energy supply station, the energy parameter adjustment model can predict the corresponding energy parameter adjustment value under the given condition. These predictions can be used to adjust the capacity of the replenishment station to meet the actual demand and to increase the efficiency of the energy replenishment.
As described in step S3 above, the training of the energy pattern adjustment model depends on various environmental conditions, equipment conditions, energy requirements, and the like. By analyzing these factors, the energy pattern adjustment model can predict the optimal energy pattern that should be taken under given conditions. For example, during peak hours, the model may suggest an energy saving mode to reduce load, while during low load periods, the model may suggest an efficient mode to increase energy utilization.
As described in the above step S4, the energy parameter adjustment value and the energy pattern adjustment value are respectively transmitted as inputs to the preset energy adjustment script. The script includes standard detection logic for the energy parameters and energy modes to verify whether the adjustment values meet preset specifications or standards. In some embodiments, this step may not be performed.
The main purpose of the energy adjustment script is to detect the energy parameter adjustment value and the energy mode adjustment value so as to ensure the operation safety and the performance optimization of the replenishment station. For example, in terms of energy parameter adjustment values, the script may detect whether the current and voltage adjustment values exceed the rated range of the replenishment station apparatus to avoid overload or damage to the electrical apparatus. Meanwhile, the energy adjustment script can also consider the sustainability requirements of the replenishment station, such as checking whether the energy parameter adjustment value meets the availability of energy resources and environmental impact.
For the energy mode adjustment value, the script can determine whether the selected energy mode matches the actual application requirement, and ensure that the replenishment station can effectively supply energy in different operation modes. For example, if the energy mode adjustment value indicates a fast charge mode, the script may check the charging device, electrical energy storage capability, and power load conditions of the replenishment station to ensure that the replenishment station is able to complete the charging task at an efficient rate.
If the detection logic in the energy adjustment script determines that the energy parameter adjustment value and the energy mode adjustment value are standard-compliant, then a value is output (e.g., validated) and vice versa, as described above in step S5.
In some embodiments, the provisioning parameters include settings or configurations in terms of attendant information, energy inventory and reserve information, convenience store merchandise information, current, voltage, frequency, etc. of the energy tender station. According to the energy parameter adjustment value, the supply parameters can be adjusted accordingly so as to achieve more efficient, stable and reliable energy supply effect. For example, if the energy parameter adjustment value indicates that an increase in charging current is required, the supply parameter may be adjusted accordingly to provide a greater charging current to the charging device, thereby increasing the charging speed. In addition, according to the energy pattern adjustment value, the supply parameter may be adjusted accordingly. For example, if the energy mode adjustment value indicates an energy saving mode, the replenishment station may correspondingly decrease the output parameter of the energy source to reduce the consumption of the energy source and be more environmentally friendly.
In this embodiment, the network model is used to perform multidimensional analysis on the energy supply information of the energy supply station, so that supply parameters are adjusted from two different dimensions of the energy parameter adjustment value and the energy mode adjustment value, and the analysis and prediction capabilities of real-time data are improved without relying on manual experience and static rules.
In an embodiment, the training process of the energy mode adjustment model includes:
acquiring energy supply training data; wherein the energy supply training data comprises a plurality of training information; training the energy pattern adjustment model requires a large amount of energy to supply training data. First, it is necessary to collect historical data of the replenishment station, including actual energy replenishment information of the replenishment station and corresponding energy pattern information to be adjusted (unnecessary information, which is not necessary if unsupervised learning is employed). The actual energy supply information of the supply station may include the input energy type of the supply station, the present current, voltage, power of the supply station, and the operating state and operating time of the supply station, etc. The energy mode information to be adjusted includes a charging mode, a power generation mode, or other energy supply modes of the replenishment station, etc.
For each energy supply training data, after hiding any training information in the energy supply training data at random each time, inputting the energy supply training data into an initial energy mode adjustment model for prediction to obtain a corresponding energy mode adjustment prediction result; and aiming at each energy supply training data, prediction is needed, and a corresponding energy mode adjustment prediction result is obtained. In order to improve the robustness and generalization capability of the model, any one training information in the energy supply training data needs to be randomly hidden, and then the rest information is input into the initial energy mode adjustment model for prediction.
And adjusting model parameters of the initial energy mode adjustment model so that training data are supplied for each energy source, and after one piece of training information is hidden, the corresponding energy mode adjustment prediction results are the same. In the prediction stage, an energy mode adjustment prediction result corresponding to the hidden training information is obtained. Then, the model parameters of the initial energy pattern adjustment model need to be adjusted so that after one training information is hidden for each energy supply training data, the corresponding energy pattern adjustment prediction result is the same as the prediction result before hiding. Specifically, optimization algorithms such as gradient descent may be used to adjust model parameters by minimizing the error of the predicted outcome from the true outcome. Through the iterative optimization process, model parameters are gradually adjusted to obtain more accurate and reliable energy mode adjustment prediction.
The training process can be repeated a plurality of times to further improve the performance of the model. By continuously collecting more energy supply training data and optimizing model parameters, the energy mode adjustment model can gradually obtain better prediction capability and generalization capability, so that the result of energy mode adjustment can be predicted more accurately.
In this embodiment, if an unsupervised learning mode is adopted, only training data needs to be supplied for each energy source, and after one piece of training information is hidden, the corresponding energy source mode adjusts the prediction result to be the same; if the supervised learning mode is adopted, the adjustment and prediction results of the corresponding energy mode are the same after one piece of training information is hidden for each piece of energy supply training data, and the adjustment and prediction results are the same as the labels corresponding to the energy supply training data.
In an embodiment, after the step of adjusting the supply parameter of the energy replenishment station based on the energy parameter adjustment value and the energy pattern adjustment value, the method further includes:
adding the actual energy supply information into a preset layer to obtain an actual energy supply picture; and adding the actual energy supply information into a preset layer to create an actual energy supply picture. The preset layer may include energy parameters, energy modes, and other related information. By adding the actual energy supply information to the layer, the information can be combined with other information (the form is not limited and will not be described here in detail), so that a picture which can visually represent the actual energy supply condition of the supply station can be formed.
Dividing the actual energy supply picture into a first picture, a second picture and a third picture; in this step, the actual energy supply picture is divided to obtain a first picture, a second picture and a third picture, which may be vertically divided into three pictures, for example. The purpose of this is to further encrypt the actual energy supply pictures and to ensure safe storage and transmission.
Encrypting the first picture, the second picture and the third picture according to a preset encryption rule; the first picture, the second picture and the third picture are different in encryption mode; and carrying out encryption processing on the first picture, the second picture and the third picture according to a preset encryption rule. The preset encryption rules may include the use of different encryption algorithms, keys and parameters. By using different encryption modes, the security of the picture can be enhanced, and unauthorized access and theft are prevented.
And storing the encrypted first picture, the encrypted second picture and the encrypted third picture into the same folder of the database. The database provides a reliable storage mode so as to store the encrypted pictures in a unified position, thereby facilitating subsequent access and management. By storing these encrypted pictures in a database, the security of the pictures can be protected and it is ensured that only authorized persons can access and use the pictures.
In an embodiment, the step of encrypting the first picture, the second picture, and the third picture according to a preset encryption rule includes:
acquiring picture parameters of the first picture; the picture parameters comprise picture data quantity, height and width, wherein the picture data quantity, the width and the height are all integers;
converting a preset coding table based on the picture data amount to obtain a conversion coding table; the conversion coding table comprises two columns, wherein one column is a number, and the other column is a character mapped with the number one by one; the converted encoding table has uniqueness and uniqueness, and can have strong data security when being encoded later. Meanwhile, the conversion process is related to the picture data quantity, is not random conversion, has strong logic and is convenient for subsequent inspection.
Coding the width and the height based on the conversion coding table respectively to obtain a width code and a height code; combining the width code and the height code to obtain a first encryption password; encrypting the first picture based on the first encryption password; and respectively encoding the width and the height according to the conversion encoding table to obtain a width code and a height code. The width code and the height code are then combined to generate a first encryption password that is used to encrypt the first picture. The encrypted first picture will be more secure against unauthorized access and theft. The above encryption process does not increase the amount of picture data.
Acquiring data information stored in a designated position of the first picture, and encoding the data information by adopting the conversion encoding table to obtain data information encoding; acquiring the creation time of the second picture; wherein the creation time includes a year; and acquiring the data information stored in the appointed position of the first picture, and encoding the data information by using a conversion encoding table to obtain the data information code. This is done to protect specific data in the first picture and to increase its security. The creation time is then encoded using a transform coding table, resulting in a time code. This time code will be used for the subsequent encryption step.
Encoding the creation time based on the conversion encoding table to obtain a time code; combining the data information code with the time code to obtain a second encryption password; encrypting the second picture based on the second encryption password; and combining the data information code and the time code to obtain a second encryption password. The second picture is encrypted based on the second encryption password. In this way, the content of the second picture can be further protected, and the security of the second picture is ensured.
Carrying out hash operation on the encrypted second picture to obtain a corresponding hash value; based on a preset character selection rule, selecting corresponding characters from the hash value to be combined, and obtaining a hash character combination; and then, carrying out hash operation on the encrypted second picture to obtain a corresponding hash value. The hash operation may be implemented by various hash algorithms, such as MD5, SHA-1, and the like. The generation of the hash value may be used for data integrity verification and identification. The selection rules of the characters can be defined according to actual requirements and security requirements.
Decoding the hash character combination based on the conversion coding table to obtain a corresponding decoding number; acquiring the resolution of the third picture, and encoding numbers in the resolution of the third picture into corresponding resolution codes based on the conversion encoding table; and combining the decoded number with the resolution code to obtain a third encryption password to encrypt the third picture.
In this embodiment, the encryption manner of encrypting the first picture, the second picture and the third picture respectively improves the security of the pictures, and meanwhile, the encryption passwords of the first picture, the second picture and the third picture are mutually associated and are mutually buckled, so that the encryption security of the pictures is improved, and the follow-up decryption by adopting the same rule is facilitated.
In an embodiment, the step of converting the preset encoding table based on the picture data amount to obtain a converted encoding table includes:
acquiring a plurality of single digits included in the picture data amount, and adding the single digits to obtain a first digit; a plurality of single digits included in the amount of picture data are acquired, and then the digits are added to obtain a first digit. This step aims to reduce the amount of picture data to a single number to facilitate subsequent processing. For example, the data amount is 254, the single number is 2, 5, 4.
Acquiring a preset encoding table, searching a first character corresponding to a first number in the encoding table, and detecting whether the character in the encoding table before the first character is larger than n; and searching a corresponding first character in the code table according to the first number. Then it is detected whether the character preceding the first character in the encoding table is greater than n, where n represents any integer. This step is to determine the position of the characters in the encoding table for subsequent movement and adjustment. Wherein n is 3.
If the number is larger than the first character, moving the first character and all the characters after the first character forward by n bits together, and sequentially translating n characters before the first character to the tail of the coding table to fill the complete coding table to obtain the conversion coding table; if the number of characters preceding the first character in the encoding table is greater than n, the first character and all characters following the first character are jointly shifted forward by n bits. The n characters preceding the first character are then sequentially translated to the end of the encoding table to populate the complete encoding table. This results in the generation of a conversion encoding table in which all n characters preceding the first character are rearranged to the end of the encoding table.
If not, the first character and all characters before the first character are jointly moved backwards by n bits, and n characters after the first character are sequentially translated to the head of the coding table so as to fill the complete coding table, and the conversion coding table is obtained. If the number of characters preceding the first character in the encoding table is not greater than n, the first character and all characters preceding the first character are shifted back by n bits together. The n characters following the first character are then translated in turn to the header of the encoding table to populate the complete encoding table. This makes it possible to generate a conversion encoding table in which n characters after the first character are rearranged to the head of the encoding table.
In this embodiment, a preset encoding table is converted into a conversion encoding table according to the amount of picture data. The conversion coding table contains specific characters mapped with numbers one by one, and the sequence and the position of the characters are adjusted according to the size of the first number. This ensures that the digits are correctly encoded into the corresponding characters during subsequent encryption and decoding processes, and that the integrity and consistency of the encoding table is maintained. Through the steps, a coding table suitable for encryption and decoding can be generated according to actual requirements, so that the uniqueness, the security and the correctness of the data are ensured.
In an embodiment, the step of converting the preset encoding table based on the picture data amount to obtain a converted encoding table includes:
acquiring a preset encoding table, and encoding the picture data amount based on the encoding table to obtain data encoding characters; wherein the data encoding characters comprise a plurality of characters; the coding table may include a plurality of characters, and the number represented by each character may be defined according to a predetermined rule. The encoding table may be constructed taking into account the readability of the characters, the size of the character set, and the uniqueness of the corresponding number. And encoding the picture data amount according to the acquired encoding table. The purpose of this step is to convert the amount of picture data into corresponding characters for subsequent processing. The coding mode can map each number to the corresponding character in the coding table and arrange the corresponding characters in a certain order.
Sequentially searching the data coding characters in the coding table and removing the data coding characters; dividing the data coding character into a first coding character and a second coding character according to a preset rule; by traversing the data encoding characters, the characters appearing in the encoding table are sequentially searched and removed. The purpose of this step is to ensure that the same characters as the data encoding characters do not appear in the encoding table to avoid duplication and collision.
And inserting the first coding character into the head part of the coding table, inserting the second coding character into the tail part of the coding table, and translating other characters in the coding table to fill the complete coding table, so as to obtain the conversion coding table. Separating the removed data coding characters according to a preset rule to obtain a first coding character and a second coding character. This separation rule may be defined according to actual requirements, for example, may be divided according to parity of the number of characters, positions of the characters, and the like. And inserting the first code character into the head of the code table and inserting the second code character into the tail of the code table according to the separated first code character and second code character. Next, a translation operation is required on the other characters in the encoding table to populate the complete encoding table. The translation may be performed according to a preset rule, for example, left translation or right translation may be performed. Through the above operation, the conversion encoding table can be obtained. The conversion code table contains all characters in the original code table, and the first code character and the second code character after separation and translation. The sequence and the content of the conversion coding table are adjusted according to preset rules, so that the conversion coding table has uniqueness, and the data security after coding is improved conveniently.
Referring to fig. 2, in an embodiment of the present invention, there is also provided an intelligent analysis system for energy supply information, including:
the energy supply system comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring actual energy supply information when the energy supply station is started and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model;
the first prediction unit is used for predicting corresponding energy parameter adjustment values according to the actual energy supply information of the energy supply station based on the energy parameter adjustment model; the energy parameter adjusting value is used for adjusting energy parameters of energy supply;
the second prediction unit is used for predicting a corresponding energy mode adjustment value according to the actual energy supply information of the energy supply station based on the energy mode adjustment model; the energy mode adjusting value is used for adjusting an energy mode of energy supply;
the judging unit is used for respectively inputting the energy parameter adjustment value and the energy mode adjustment value into a preset energy adjustment script as input parameters and judging whether the corresponding values can be output or not; the preset energy adjustment script comprises detection logic for detecting whether an energy parameter adjustment value and an energy mode adjustment value meet standards or not;
And the adjusting unit is used for adjusting the supply parameters of the energy supply station based on the energy parameter adjusting value and the energy mode adjusting value if the corresponding values can be output.
In this embodiment, for specific implementation of each unit in the above embodiment of the apparatus, please refer to the description in the above embodiment of the method, and no further description is given here.
Referring to fig. 3, in an embodiment of the present invention, there is further provided a computer device, which may be a server, and an internal structure thereof may be as shown in fig. 3. The computer device includes a processor, a memory, a display screen, an input device, a network interface, and a database connected by a system bus. Wherein the computer is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store the corresponding data in this embodiment. The network interface of the computer device is used for communicating with an external terminal through a network connection. Which computer program, when being executed by a processor, carries out the above-mentioned method.
It will be appreciated by those skilled in the art that the architecture shown in fig. 3 is merely a block diagram of a portion of the architecture in connection with the present inventive arrangements and is not intended to limit the computer devices to which the present inventive arrangements are applicable.
An embodiment of the present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above method. It is understood that the computer readable storage medium in this embodiment may be a volatile readable storage medium or a nonvolatile readable storage medium.
In summary, the method and system for intelligent analysis of energy supply information provided in the embodiment of the invention include: when an energy supply station is started, acquiring actual energy supply information when the energy supply station is started, and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model; based on the energy parameter adjustment model, predicting corresponding energy parameter adjustment values according to actual energy supply information of the energy supply station; the energy parameter adjusting value is used for adjusting energy parameters of energy supply; based on the energy mode adjustment model, predicting a corresponding energy mode adjustment value according to actual energy supply information of the energy supply station; the energy mode adjusting value is used for adjusting an energy mode of energy supply; respectively taking the energy parameter adjustment value and the energy mode adjustment value as input parameters to a preset energy adjustment script, and judging whether the corresponding values can be output or not; the preset energy adjustment script comprises detection logic for detecting whether an energy parameter adjustment value and an energy mode adjustment value meet standards or not; and if the corresponding value can be output, adjusting the supply parameter of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value. According to the invention, the actual energy supply information is predicted through the trained network model to obtain the energy parameter adjustment value and the energy mode adjustment value, so that the supply parameters are adjusted without depending on artificial experience and static rules, and the analysis and prediction capability of real-time data is improved.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium provided by the present invention and used in embodiments may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM, among others.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes using the descriptions and drawings of the present invention or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (9)
1. An intelligent analysis method for energy supply information is characterized by comprising the following steps:
when an energy supply station is started, acquiring actual energy supply information when the energy supply station is started, and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model;
Based on the energy parameter adjustment model, predicting corresponding energy parameter adjustment values according to actual energy supply information of the energy supply station; the energy parameter adjusting value is used for adjusting energy parameters of energy supply;
based on the energy mode adjustment model, predicting a corresponding energy mode adjustment value according to actual energy supply information of the energy supply station; the energy mode adjusting value is used for adjusting an energy mode of energy supply;
and adjusting the supply parameters of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value.
2. The intelligent analysis method of energy supply information according to claim 1, wherein the training process of the energy pattern adjustment model includes:
acquiring energy supply training data; wherein the energy supply training data comprises a plurality of training information;
for each energy supply training data, after hiding any training information in the energy supply training data at random each time, inputting the energy supply training data into an initial energy mode adjustment model for prediction to obtain a corresponding energy mode adjustment prediction result;
and adjusting model parameters of the initial energy mode adjustment model so that training data are supplied for each energy source, and after one piece of training information is hidden, the corresponding energy mode adjustment prediction results are the same.
3. The intelligent analysis method of energy supply information according to claim 1, wherein after the step of adjusting the supply parameters of the energy supply station based on the energy parameter adjustment value and the energy pattern adjustment value, the intelligent analysis method comprises:
adding the actual energy supply information into a preset layer to obtain an actual energy supply picture;
dividing the actual energy supply picture into a first picture, a second picture and a third picture;
encrypting the first picture, the second picture and the third picture according to a preset encryption rule; the first picture, the second picture and the third picture are different in encryption mode;
and storing the encrypted first picture, the encrypted second picture and the encrypted third picture into the same folder of the database.
4. The intelligent analysis method of energy supply information according to claim 3, wherein the step of encrypting the first picture, the second picture, and the third picture according to a preset encryption rule, respectively, includes:
acquiring picture parameters of the first picture; the picture parameters comprise picture data quantity, height and width, wherein the picture data quantity, the width and the height are all integers;
Converting a preset coding table based on the picture data amount to obtain a conversion coding table; the conversion coding table comprises two columns, wherein one column is a number, and the other column is a character mapped with the number one by one;
coding the width and the height based on the conversion coding table respectively to obtain a width code and a height code; combining the width code and the height code to obtain a first encryption password; encrypting the first picture based on the first encryption password;
acquiring data information stored in a designated position of the first picture, and encoding the data information by adopting the conversion encoding table to obtain data information encoding; acquiring the creation time of the second picture; wherein the creation time includes a year;
encoding the creation time based on the conversion encoding table to obtain a time code; combining the data information code with the time code to obtain a second encryption password; encrypting the second picture based on the second encryption password;
carrying out hash operation on the encrypted second picture to obtain a corresponding hash value; based on a preset character selection rule, selecting corresponding characters from the hash value to be combined, and obtaining a hash character combination;
Decoding the hash character combination based on the conversion coding table to obtain a corresponding decoding number; acquiring the resolution of the third picture, and encoding numbers in the resolution of the third picture into corresponding resolution codes based on the conversion encoding table; and combining the decoded number with the resolution code to obtain a third encryption password to encrypt the third picture.
5. The intelligent analysis method of energy supply information according to claim 4, wherein the step of converting a preset encoding table based on the picture data amount to obtain a converted encoding table includes:
acquiring a plurality of single digits included in the picture data amount, and adding the single digits to obtain a first digit;
acquiring a preset encoding table, searching a first character corresponding to a first number in the encoding table, and detecting whether the character in the encoding table before the first character is larger than n;
if the number is larger than the first character, moving the first character and all the characters after the first character forward by n bits together, and sequentially translating n characters before the first character to the tail of the coding table to fill the complete coding table to obtain the conversion coding table;
If not, the first character and all characters before the first character are jointly moved backwards by n bits, and n characters after the first character are sequentially translated to the head of the coding table so as to fill the complete coding table, and the conversion coding table is obtained.
6. The intelligent analysis method of energy supply information according to claim 4, wherein the step of converting a preset encoding table based on the picture data amount to obtain a converted encoding table includes:
acquiring a preset encoding table, and encoding the picture data amount based on the encoding table to obtain data encoding characters; wherein the data encoding characters comprise a plurality of characters;
sequentially searching the data coding characters in the coding table and removing the data coding characters; dividing the data coding character into a first coding character and a second coding character according to a preset rule;
and inserting the first coding character into the head part of the coding table, inserting the second coding character into the tail part of the coding table, and translating other characters in the coding table to fill the complete coding table, so as to obtain the conversion coding table.
7. The intelligent analysis method according to claim 1, wherein the step of adjusting the supply parameters of the energy supply station based on the energy parameter adjustment value and the energy pattern adjustment value includes, before:
respectively taking the energy parameter adjustment value and the energy mode adjustment value as input parameters to a preset energy adjustment script, and judging whether the corresponding values can be output or not; the preset energy adjustment script comprises detection logic for detecting whether an energy parameter adjustment value and an energy mode adjustment value meet standards or not;
and if the corresponding value can be output, executing the step of adjusting the supply parameter of the energy supply station based on the energy parameter adjustment value and the energy mode adjustment value.
8. An intelligent analysis system for energy supply information, comprising:
the energy supply system comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring actual energy supply information when the energy supply station is started and inputting the actual energy supply information into an energy network model; the energy network model comprises an energy parameter adjustment model and an energy mode adjustment model;
The first prediction unit is used for predicting corresponding energy parameter adjustment values according to the actual energy supply information of the energy supply station based on the energy parameter adjustment model; the energy parameter adjusting value is used for adjusting energy parameters of energy supply;
the second prediction unit is used for predicting a corresponding energy mode adjustment value according to the actual energy supply information of the energy supply station based on the energy mode adjustment model; the energy mode adjusting value is used for adjusting an energy mode of energy supply;
and the adjusting unit is used for adjusting the supply parameters of the energy supply station based on the energy parameter adjusting value and the energy mode adjusting value.
9. A computer device comprising a memory and a processor, the memory having stored therein a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
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