CN113298281B

CN113298281B - Resource processing method, device, equipment and machine readable medium

Info

Publication number: CN113298281B
Application number: CN202011005888.XA
Authority: CN
Inventors: 毛宏举; 程明; 吕畅; 孟晓林; 王加龙; 李湛; 王冠
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2020-09-22
Filing date: 2020-09-22
Publication date: 2022-11-22
Anticipated expiration: 2040-09-22
Also published as: CN113298281A

Abstract

The embodiment of the application provides a resource processing method, a device, equipment and a machine readable medium, wherein the method comprises the following steps: collecting resource cost data; the resource cost data includes at least one of: value data and transaction data; and determining resource cost data corresponding to the use objects of at least one use object type according to the resource cost data. According to the embodiment of the application, the coverage rate, the fine granularity and the flexibility of the resource cost data can be improved, and further the processing efficiency and the processing accuracy of the resources can be improved.

Description

Resource processing method, device, equipment and machine readable medium

Technical Field

The present application relates to the field of resource processing technologies, and in particular, to a resource processing method, a resource processing apparatus, a device, and a machine-readable medium.

Background

Electric power refers to the ability to use electricity to do work in various forms (i.e., produce energy). Electric power is widely applied to various fields such as power, illumination, chemistry, spinning, communication, broadcasting and the like, and is a main power for scientific and technical development and economic leap.

At present, more and more enterprises, organizations and other units begin to establish their own data centers to support the processing of resources such as power and further improve the processing efficiency of the resources. The data center can collect and provide operation data such as electric power, electric quantity and electricity utilization rate corresponding to the electricity utilization facilities so that users can know the operation conditions corresponding to the electricity utilization facilities.

In the implementation of the embodiments of the present application, the inventor finds that, in order to improve the processing efficiency of the power, the user generally needs to use other data besides the operation data. However, the current data center only provides operation data, in which case, the user usually needs to acquire other data manually, which makes the processing efficiency of the power low.

Disclosure of Invention

The technical problem to be solved by the embodiments of the present application is to provide a resource processing method, which can improve coverage, fine granularity and flexibility of resource cost data, and further can improve processing efficiency and processing accuracy of resources.

Correspondingly, the embodiment of the application also provides a resource processing device, equipment and a machine readable medium, which are used for ensuring the realization and the application of the method.

In order to solve the above problem, an embodiment of the present application discloses a resource processing method, including:

collecting resource cost data; the resource cost data includes at least one of: value data and transaction data;

and determining resource cost data corresponding to the use object of at least one use object type according to the resource cost data.

On the other hand, the embodiment of the application also discloses a resource processing method, which comprises the following steps:

determining a prediction result of the resource consumption information;

and determining transaction information corresponding to the use object according to the resource cost data, the historical resource consumption data and the prediction result corresponding to the use object of at least one use object type.

On the other hand, the embodiment of the present application further discloses a resource processing apparatus, including:

a collection module for collecting resource cost data; the resource cost data includes at least one of: value data and transaction data;

and the determining module is used for determining resource cost data corresponding to the use object of at least one use object type according to the resource cost data.

the prediction result determining module is used for determining the prediction result of the resource consumption information;

and the transaction information determining module is used for determining the transaction information corresponding to the use object according to the resource cost data, the historical resource consumption data and the prediction result corresponding to the use object of at least one use object type.

In another aspect, an embodiment of the present application further discloses an apparatus, including:

one or more processors; and

one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform one or more of the methods described above.

In yet another aspect, embodiments of the present application disclose one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform one or more of the foregoing methods.

The embodiment of the application has the following advantages:

the embodiment of the application collects the resource cost data, and can summarize the resource cost data so as to improve the coverage rate of the resource cost data. The resource cost data can be processed to obtain the resource cost data corresponding to the use object of at least one use object type, and the resource cost data can be provided according to the use object type, so that the fine granularity and flexibility of the resource cost data can be improved, and the cost data acquisition requirements of users in different dimensions can be met. For example, the embodiment of the present application may maintain electricity cost data of a certain device in a time dimension according to an identifier of the device; for another example, in the embodiment of the present application, power consumption cost data of all devices in a certain campus in a time dimension may be maintained according to an identifier of the campus.

In addition, under the condition of improving the coverage rate and fine granularity of the resource cost data, the resource cost data can be used in the resource processing process, so that the processing efficiency and the processing accuracy of the resources can be improved. For example, the resource cost data may be applied to resource processing processes such as cost accounting, cost optimization, transaction processing, and the like to reduce resource costs or to improve transaction efficiency and transaction revenue.

Drawings

FIG. 1 is a flowchart illustrating steps of a first embodiment of a resource processing method according to the present application;

FIG. 2 is an illustration of resource cost data in an embodiment of the application;

FIG. 3 is an illustration of electrical operating data of an embodiment of the present application;

FIG. 4 is a flowchart illustrating steps of a third embodiment of a resource processing method according to the present application;

FIG. 5 is a flowchart illustrating the fourth step of an embodiment of a resource processing method according to the present application;

FIG. 6 is an illustration of a power transaction process according to an embodiment of the present application;

FIG. 7 is an illustration of a service process of an embodiment of the present application;

FIG. 8 is a schematic representation of presentation data in accordance with an embodiment of the present application;

FIG. 9 is a block diagram of an embodiment of a resource processing apparatus of the present application;

FIG. 10 is a schematic structural diagram of an embodiment of a resource processing apparatus according to the present application;

FIG. 11 is a block diagram of an embodiment of a resource processing apparatus of the present application; and

fig. 12 is an exemplary device 1300 that may be used to implement the various embodiments described above in this application.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application are within the scope of protection of the present application.

While the concepts of the present application are susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the description above is not intended to limit the application to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the application.

Reference in the specification to "one embodiment," "an embodiment," "a particular embodiment," or the like, means that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may or may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, where a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described. In addition, it should be understood that items in the list included in the form "at least one of a, B, and C" may include the following possible items: (A); (B); (C); (A and B); (A and C); (B and C); or (A, B and C). Likewise, an item listed in the form "at least one of a, B, or C" may mean (a); (B); (C); (A and B); (A and C); (B and C); or (A, B and C).

In some cases, the disclosed embodiments may be implemented as hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried or stored in one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be executed by one or more processors. A machine-readable storage medium may be implemented as a storage device, mechanism, or other physical structure (e.g., a volatile or non-volatile memory, a media disk, or other media other physical structure device) for storing or transmitting information in a form readable by a machine.

In the drawings, some structural or methodical features may be shown in a particular arrangement and/or ordering. Preferably, however, such specific arrangement and/or ordering is not necessary. Rather, in some embodiments, such features may be arranged in different ways and/or orders than as shown in the figures. Moreover, the inclusion of structural or methodological features in a particular figure is not meant to imply that such features are required in all embodiments, and in some embodiments, may not be included or may be combined with other features.

The method and the device can be used for processing resources of enterprises, institutions and other units. The above resources may be a general term for various material elements such as material resources, financial resources, and manpower owned by a unit. The resources may include: the power, water power, gas resources, carbon resources, software and hardware resources of the computer, and the like, it can be understood that any resource is within the scope of protection of the resources of the embodiments of the present application.

In the conventional art, the data center only provides the operation data, and in this case, the user usually needs to acquire the resource cost data in a manual mode. For example, manually searching resource cost data on a webpage; or, a manual transmission mode is adopted to transmit the resource cost data among different users. The manual mode makes the processing efficiency of the electric power lower.

Aiming at the technical problems that the current data center only provides operation data and the processing efficiency of electric power is low, the embodiment of the application provides a resource processing scheme, and the scheme specifically comprises the following steps: collecting resource cost data; the resource cost data includes at least one of: value data and transaction data; and determining resource cost data corresponding to the use objects of at least one type of use object according to the resource cost data.

In the embodiment of the application, the use object can represent the object of the use resource. Taking an electric power resource as an example, the usage object may be an electric utility.

The usage object class may characterize the class of usage objects, which may characterize different usage objects from different thinking perspectives. For example, the usage object type specifically includes at least one of the following: areas, cities, parks, machine rooms, bays, racks, equipment, and the like.

The region may represent a geographic region, which may be a region where a country is located globally or a region where a city is located in a country. The district can represent that administrative agency concentrates on unified planning appointed region, and enterprise, company etc. that set up certain type of specific trade, form specially in the region carry out unified management, and is typical like the industry garden, trade garden, industry garden, animation garden etc.. The machine room can represent workplaces and production units. In the field of communications, a computer room may characterize a place where a server is stored to provide a service. The cubicle may characterize the room comprised by the machine room. The rack is used for bearing equipment. The apparatus may include: a server, etc.

The embodiment of the application collects the resource cost data, and can summarize the resource cost data so as to improve the coverage rate of the resource cost data. The resource cost data can be processed to obtain the resource cost data corresponding to the use object of at least one use object type, and the resource cost data can be provided according to the use object type, so that the fine granularity and the flexibility of the resource cost data can be improved, and the cost data acquisition requirements of users in different dimensions can be met. For example, the embodiment of the present application may maintain electricity cost data of a certain device in a time dimension according to an identifier of the device; for another example, in the embodiment of the present application, power consumption cost data of all devices in a certain campus in a time dimension may be maintained according to an identifier of the campus.

The time dimension of the embodiment of the application can correspond to any time dimension, such as year, month, day, hour, minute, and even life cycle, so that the precision of the resource cost data can be improved.

Method embodiment one

Referring to fig. 1, a flowchart illustrating steps of a first embodiment of a resource processing method according to the present application is shown, where the method may specifically include the following steps:

step 101, collecting resource cost data; the resource cost data specifically includes at least one of the following: value data and transaction data;

step 102, determining resource cost data corresponding to the use object of at least one use object type according to the resource cost data.

At least one step included in the method of the embodiment of the present application may be executed by a resource processing apparatus, and the resource processing apparatus may process a resource corresponding to a unit, and may provide a resource service to a user, so that processing efficiency of the resource may be improved.

In step 101, the value data may represent a conversion form obtained by the resource in the circulation process, specifically, the amount of money required by the resource in the circulation process. The value data may be unit value data, that is, value data corresponding to a unit of resource. Alternatively, the value data may be consumption value data, i.e., value data corresponding to resources consumed in a time dimension.

In the conventional technology, a data center of a unit generally acquires operation data of an electric facility in an acquisition mode. The data center is isolated from the data source of the resource cost data, so that the data center does not have the acquisition capability of the resource cost data.

The embodiment of the application can establish the association between the data sources of the resource cost data, and determine the resource cost data corresponding to the use object of at least one use object type according to the association.

Accordingly, the embodiment of the present application may provide the following collection manner, to collect the resource cost data corresponding to the usage object of at least one usage object type:

the method comprises the following steps of 1, crawling resource cost data from a third-party platform; or

A collection mode 2, acquiring resource cost data from the financial data; or

And 3, performing text recognition and semantic recognition on the non-text format file to obtain resource cost data.

For collection mode 1, the third party platform may be a platform other than the resource handling device. The third party platform may be a common resource platform, such as a power supply platform. The resource platform may include: unit value data with stronger timeliness. Alternatively, the resource platform may include: consumption value data for a unit submission.

According to the method and the device, a webpage crawling mode can be adopted, and the resource cost data can be crawled from the webpage of the third-party platform, so that the isolation between the resource processing device and the third-party platform is broken through.

For collection mode 2, the financial data may characterize the unit's currency-related data, and the financial data may include: resource cost data.

Financial data is typically affiliated with a financial system, with privacy and is not disclosed to the outside. The embodiment of the application can break privacy limitation of the financial data, cooperate with the financial system and acquire resource cost data from the financial data.

For collection mode 3, the data obtained from the third party platform or financial data may include files in non-textual format. The non-text format may include: picture Format, PDF (Portable Document Format), etc., which generally cannot be directly recognized.

The embodiment of the application can perform text Recognition on the file in the non-text format by using an OCR (Optical Character Recognition) technology to obtain the text contained in the file.

The embodiment of the application can also perform semantic recognition on the text contained in the file to obtain corresponding resource cost data. The corresponding semantic recognition technique may include: natural language understanding techniques, such as syntactic analysis techniques, deep learning techniques, and the like.

For example, the consumption value data are of a plurality of types, and in the embodiment of the application, different types of consumption value data, such as capacity electricity charge data, commercial power electricity charge data, and the like, can be obtained according to a semantic recognition technology.

In this embodiment of the application, optionally, the type of the usage object specifically includes at least one of the following: areas, cities, parks, machine rooms, bays, racks, equipment, and the like. According to the embodiment of the application, the corresponding resource cost data can be determined and stored aiming at least one type of using object.

In step 102, the embodiment of the present application may provide the following determination manner to determine the resource cost data corresponding to the usage object of at least one usage object type:

determining a mode 1, and determining resource cost data corresponding to a use object of a first use object type; or

The specifying method 2 specifies the resource cost data corresponding to the object to be used of the second object type based on the resource cost data corresponding to the object to be used of the first object type and the consumption parameter corresponding to the object to be used of the second object type included in the first object type.

The determination method 1 may be applied to a use object capable of directly determining resource cost data, and may be applied to a use object such as an area, a city, a campus, a machine room, a booth, and a rack.

Alternatively, the resource cost data obtained in step 101 may be analyzed to extract resource cost data corresponding to the usage object of the first usage object type. Specifically, the corresponding resource cost data may be extracted according to the keyword of the first usage object type. For example, the resource cost data corresponding to the keywords in the collection methods 1 to 3 may be located according to the keywords of the first usage object type.

The determination method 2 is applicable to a use object for which the resource cost data cannot be directly determined, and is applicable to a use object such as a server.

The determination method 2 may allocate the resource cost data corresponding to the usage object of the first usage object type according to the consumption parameter corresponding to the usage object of the second usage object type, so as to obtain the resource cost data corresponding to the usage object of the second usage object type.

The consumption parameter may be related to consumption of a resource, e.g., consumption of power is related to a power parameter, so that the cost data for a rack may be assigned to the power parameter of an individual server based on the power parameters of the servers within the rack.

It can be understood that, according to actual application requirements, a person skilled in the art may determine resource cost data corresponding to a usage object of at least one usage object type by using any one or a combination of the determination method 1 to the determination method 2, or by using other determination methods.

Referring to fig. 2, an illustration of resource cost data of an embodiment of the present application is shown. The resource cost data may correspond to power, and specifically includes: the corresponding data sources may include: a third party platform and a financial system.

The page corresponding to the resource cost data may include: a data filling condition statistics page, an electric quantity page and an electric charge page corresponding to various types of the objects to be used. According to the method and the device, the resource cost data can be extracted from the page, the extracted resource cost data can be checked, and if the check is passed, the checked resource cost data can be stored. If the check fails, a modification request can be sent to the corresponding data source to modify the resource cost data.

In an optional embodiment of the present application, a query interface corresponding to the resource cost data may be further provided for the at least one usage object category.

The query interface is available for invocation to provide a query service for the resource cost data. The query interface may be arranged in a page for user triggering. Under the condition that a user triggers a query interface in a page, a corresponding query request can be obtained.

In this embodiment of the present application, optionally, the mapping relationship between the resource identifier and the resource cost data may be saved, and then, according to the query request, the mapping relationship may be searched, and the resource cost data obtained by the search may be returned as a query result.

In the embodiment of the present application, optionally, the requesting user corresponding to the query request may be authenticated, where the authentication may be used to determine whether the requesting user has a query right for the use object, and if the authentication passes, the query result is returned to the requesting user, and if the authentication does not pass, the query result is not returned to the requesting user, so that the security of the resource cost data may be improved.

In the embodiment of the present application, optionally, resource cost data of the resource identifier in any time dimension may also be provided. The time dimension may correspond to any time dimension, such as year, month, day, hour, minute, or even life cycle, which may improve the accuracy of the resource cost data. Correspondingly, the embodiment of the application can store the mapping relation among the resource identification, the time dimension and the resource cost data.

In this embodiment of the present application, optionally, resource cost data corresponding to multiple usage objects in a unit may also be fused, so as to implement global information of the resource cost data.

In summary, the resource processing method of the embodiment of the present application collects the resource cost data, and can summarize the resource cost data to improve the coverage rate of the resource cost data. The resource cost data can be processed to obtain the resource cost data corresponding to the use object of at least one use object type, and the resource cost data can be provided according to the use object type, so that the fine granularity and the flexibility of the resource cost data can be improved, and the cost data acquisition requirements of users in different dimensions can be met. For example, the embodiment of the present application may maintain electricity cost data of a certain device in a time dimension according to an identifier of the device; for another example, in the embodiment of the present application, power consumption cost data of all devices in a certain campus in a time dimension may be maintained according to an identifier of the campus.

In addition, the embodiment of the application can provide the query interface corresponding to the resource cost data, so that the resource cost data corresponding to the object can be conveniently queried, and the resource cost data acquisition efficiency can be improved. For the user, the user can query the resource cost data corresponding to the usage object of the usage object category through the identification of the usage object. For example, a user may query for electricity cost data for a device in a time dimension using an identification of the device. Alternatively, the user may use the identifier of a certain campus to query and obtain the electricity cost data of all the devices in the campus in one time dimension.

Method embodiment two

With respect to the first embodiment of the method shown in fig. 1, the method of this embodiment may further include: determining operation data corresponding to the use object of at least one use object type; and providing a query interface corresponding to the running data.

The embodiment of the application can provide query service corresponding to the running data. The embodiment of the application can support the query of real-time operation data and historical operation data in any time dimension.

Referring to fig. 3, an illustration of electrical operating data of an embodiment of the present application is shown. The real-time operation data or the historical operation data can be processed correspondingly according to the use objects in the self-built base or the rented machine room. The real-time operation data may include: real-time total power, real-time load rate, real-time power, etc., it can be understood that the embodiment of the present application does not impose any limitation on specific real-time operation data.

Method example III

Referring to fig. 4, a flowchart illustrating steps of a third embodiment of the resource processing method according to the present application is shown, where the method may specifically include the following steps:

step 401, collecting resource cost data; the resource cost data specifically includes at least one of the following: value data and transaction data;

step 402, determining resource cost data corresponding to the use object of at least one use object type according to the resource cost data;

with respect to the first embodiment of the method shown in fig. 1, the method of this embodiment may further include:

step 403, determining historical resource consumption data corresponding to the use object of at least one use object type;

step 404, predicting resource consumption information of the object of use of the at least one kind of object of use in at least one time dimension according to the historical resource consumption data and the environment parameter of the object of use.

In the embodiment of the application, the resource consumption information can be predicted in any time dimension, such as power utilization prediction in dimensions of hours, days, months and the like.

The electricity utilization prediction is the premise and the basis of the power processing, and the accuracy of the electricity utilization prediction is directly related to the accuracy of the power processing and the safe and economic operation of a unit. Taking the power processing and maintenance of power transaction as an example, the accuracy of power utilization prediction also relates to transaction results such as transaction efficiency and transaction income.

According to the resource consumption data and the environmental parameters of the using objects, the resource consumption information of the using objects in at least one time dimension is predicted. The historical resource consumption data can be actual operation data of the use object in a past period of time, for example, resource consumption information of the use object in one time dimension in a preset period of time, such as electricity consumption of a machine room in a month in a day dimension, and the like. The historical resource consumption data can reflect the rule of the resource consumption information of the using object, and therefore can be used as a basis for prediction.

And, the environment parameter may represent an environment in which the usage object is located, and the environment parameter may affect resource consumption information of the usage object. According to the embodiment of the application, the environment parameters are applied to the prediction process, so that the prediction precision can be improved.

Optionally, the environmental parameter specifically includes at least one of the following: physical environment parameters, lifecycle parameters, and on-shelf parameters of the object of use.

The physical environment parameters may include: temperature, humidity, etc. Typically, different physical parameters may correspond to different amounts of power usage and thus may be used to predict the amount of power usage.

The lifecycle parameters may characterize the lifecycle of the resource system, such as the initial stage of production, the middle stage of production, and so on. Often different lifecycle parameters may correspond to different power usage. For example, the utilization rate of resources at the initial stage of production is low, and therefore the amount of electricity used is relatively low. And in the middle and later periods of production, the utilization rate of resources is higher, so that the power consumption is relatively high.

The on-shelf parameters of the used objects can represent the configuration rate of the equipment, and the utilization rate of electric quantity can be reflected to a certain degree. Under the condition of lower overhead rate, it is shown that more devices can be added, so that the growth space of resource consumption is larger. For example, in the case of the rack rate of 50%, the used amount of electricity is 50 ten thousand degrees, and in the case of the rack rate of 80%, the used amount of electricity may increase to 80 ten thousand degrees or more.

In summary, the embodiment of the present application may apply the environmental parameter to the prediction process by using the correlation between the environmental parameter and the resource consumption information, and may reflect the change of the environmental parameter to the prediction result. Since the change of the environmental parameter can be converted into a change corresponding to the prediction result, the accuracy of the prediction result can be improved.

According to the embodiment of the application, the prediction result corresponding to the use object can be determined according to the mapping relation among the historical resource consumption data, the environmental parameter and the resource consumption information.

Alternatively, the mapping relationship between the historical resource consumption data, the environmental parameter, and the resource consumption information may be characterized by a data analyzer. Correspondingly, the method may further include: training the training data to obtain a data analyzer; the data analyzer may be configured to characterize mapping relationships between historical resource consumption data, environmental parameters, and resource consumption information; the training data may include: historical resource consumption data.

In an alternative embodiment of the present application, the mathematical model may be trained based on training data to obtain a data analyzer, and the data analyzer may characterize a mapping relationship between input data (historical resource consumption data and environmental parameters) and output data (predicted results), so as to determine the predicted results based on the input historical resource consumption data and the environmental parameters.

The mathematical model is a scientific or engineering model constructed by using a mathematical logic method and a mathematical language, and is a mathematical structure which is generally or approximately expressed by adopting the mathematical language aiming at the characteristic or quantity dependency relationship of a certain object system, and the mathematical structure is a relationship structure which is described by means of mathematical symbols. The mathematical model may be one or a set of algebraic, differential, integral or statistical equations, and combinations thereof, by which the interrelationships or causal relationships between the variables of the system are described quantitatively or qualitatively. In addition to mathematical models described by equations, there are also models described by other mathematical tools, such as algebra, geometry, topology, mathematical logic, etc. Where the mathematical model describes the behavior and characteristics of the system rather than the actual structure of the system. The method can adopt methods such as machine learning and deep learning methods to train the mathematical model, and the machine learning method can comprise the following steps: linear regression, decision trees, random forests, etc., and the deep learning method may include: convolutional Neural Networks (CNN), long-short Term Memory Networks (LSTM), gated cyclic units (GRU), and so on.

According to the method and the device, the parameters of the data analyzer can be adjusted according to the deviation between the historical resource consumption data and the prediction result. For example, the time dimension is day, a corresponding deviation can be determined for the prediction result corresponding to the day dimension and the historical resource consumption information corresponding to the day dimension, and the parameter of the data analyzer is adjusted according to the deviation, so as to reduce the deviation and improve the accuracy of the prediction result.

According to the embodiment of the application, the time dimension can be determined according to the actual application requirement.

Taking the power resource as an example, the corresponding transaction may include: a first transaction and a second transaction. Wherein the first transaction and the second transaction may correspond to different time dimensions. For example, the first time dimension corresponding to the first transaction may be a year or a month, and the first transaction may be referred to as a medium-and-long term transaction; the second time dimension for the second transaction may be a day or an hour, and the second transaction may be referred to as a spot transaction.

According to the embodiment of the application, the prediction result corresponding to the first time dimension can be determined by using historical resource consumption data and environmental parameters corresponding to the year or the month, and the prediction result corresponding to the first time dimension is applied to the first transaction, so that the efficiency and the transaction result of the first transaction are improved.

According to the embodiment of the application, the prediction result corresponding to the second time dimension can be determined by using historical resource consumption data and environmental parameters corresponding to the year or the month, and the prediction result corresponding to the second time dimension is applied to the second transaction, so that the efficiency and the transaction income of the second transaction are improved.

Besides determining the transaction varieties according to the time dimension, the embodiment of the application can also determine the transaction varieties according to the types of the electric power. For example, transaction varieties may include: and the thermal power, wind power, hydropower and new energy varieties respectively correspond to the transaction varieties.

Besides determining the transaction varieties according to the time dimension, the embodiment of the application can also determine the transaction varieties according to the varieties of transaction forms. For example, transaction varieties may include: trade varieties such as bilateral trade, bid price and listing.

Method example four

Referring to fig. 5, a flowchart illustrating a fourth step of an embodiment of a resource processing method according to the present application is shown, where the method may specifically include the following steps:

step 501, determining a prediction result of resource consumption information;

step 502, determining transaction information corresponding to the object of use according to the resource cost data, the historical resource consumption data and the prediction result corresponding to the object of use of at least one type of object of use.

According to the method and the device, the prediction result of the resource consumption information is used in the determining process of the transaction information, and the transaction information can help the user determine the transaction information such as transaction parameters, transaction result information and the like, so that the transaction efficiency, the transaction benefits and the like can be improved.

The transaction of the embodiment of the application can comprise the following steps: resource purchases, resource transfers, etc. The transaction information can be determined by combining real-time unit value data in the resource cost data corresponding to the object to be used, so that the transaction income is improved.

The transaction information in the embodiment of the present application may include at least one of the following: supply and demand information, transaction process information and transaction result information.

The supply and demand information may reflect supply and demand information of resources in the preset area. The supply and demand information may include: the resource supply information may be information about a supply and demand relationship between resources supplied in a preset area, or resources required in the preset area, or resources supplied in the preset area and resources required in the preset area, where the supply and demand relationship information may be greater than, less than, or equal to the above.

The preset area may be a first preset area with a large range, such as a national area or a city-saving area. The supply-demand relationship information of the resources in the first preset area can influence the unit value data of the resources. For example, the supply-demand relationship information may be a ratio of supply to demand, and generally, the larger the ratio, the smaller the corresponding unit value data.

The preset area can also be a second preset area corresponding to the unit. In this case, the resources provisioned may include: an existing resource or an existing resource within the second predetermined area. Optionally, the resource corresponding to the first transaction may be converted from the first time dimension to the second time dimension to obtain the resource corresponding to the first transaction in the second time dimension, which may be referred to as a conversion resource. For example, power purchased annually or monthly may be converted to resources corresponding to days or hours to obtain conversion resources. The resources of the demand may include: and resources corresponding to the prediction result.

The embodiment of the application can compare the conversion resource with the prediction result to obtain the supply and demand relation information. The supply-demand relationship information may be used to determine a transaction type (e.g., transfer or purchase), or transaction amount data (i.e., how much of the amount of resources are transferred or purchased).

The transaction process information may include: transaction unit value data and transaction amount data. It is to be appreciated that different time dimensions may correspond to different transaction process information. Taking daily transactions as an example, different hours of dimensions may correspond to different transaction process information during a day.

The transaction result information may include: transaction benefit information. The transaction revenue information may include: a trade income corresponding to trade process information. For example, in the case where the transaction unit value data for a completed transaction is less than the real-time unit value data, the existing resources are transferred and the corresponding transaction revenue can be generated.

Alternatively, the transaction revenue information may include: and difference information of the transaction total value data corresponding to the various transaction process information. Taking daily transaction as an example, different hour dimensions in a day can correspond to different transaction process information, and transaction value data corresponding to all hour dimensions in a day are fused to obtain the total transaction value data. The transaction total value data corresponding to the various transaction process information are compared, and the transaction process information with better transaction income can be determined according to the transaction total value data and used for the final transaction process.

In this embodiment of the application, optionally, the determining the transaction information corresponding to the use object specifically includes:

determining allocation information between the first transaction and the second transaction corresponding to the use object, for example, resource consumption information corresponding to medium-and-long-term transactions and spot transactions can be allocated to improve transaction benefits and reduce transaction cost; or alternatively

Determining the information of the first transaction or the information of the second transaction corresponding to the using object, and determining the supply and demand information, the transaction process information and the transaction result information corresponding to the first transaction or the second transaction; or

And determining the transaction result information respectively corresponding to the use objects under the condition of various transaction process information.

In one embodiment of the present application, the resource may be electricity, and the transaction may be a transaction corresponding to a target transaction day. The process of determining transaction information may include: determining daily electricity consumption data (e.g., an actual daily load curve) from the historical resource consumption data; obtaining an electric quantity prediction time-sharing curve of the target trading day according to the prediction result of the resource consumption information of the target trading day; and determining the transaction process information of the target transaction day according to the daily load curve, the electric quantity forecasting time-sharing curve, the historical transaction data, the environmental parameters of the target transaction day and other data.

Optionally, a variety of transaction process information may be determined. For example, a plurality of transaction process information may be determined according to different bidding strategies (e.g., aggressive, conservative, robust strategies), and different transaction process information may correspond to different transaction value data or transaction amount data. According to the method and the device, the target transaction process information can be determined from the multiple transaction process information according to the transaction result information corresponding to the use object under the condition of the multiple transaction process information, and the target transaction process information can be selected and used by the user. The method can help the user to determine the target transaction process information with higher quality of the transaction result, so that the operation cost of the user can be saved, and the transaction efficiency is improved. In addition, the target transaction process information is objectively determined according to various data, so that the objectivity and the accuracy of the transaction process information can be improved.

In an example of the present application, assuming that a large number of servers will be on the shelf in three days in the future in a certain usage object dimension, and the electric quantity will increase rapidly, in order to realize the transaction result information of the preset condition, the electricity prediction results corresponding to the three days in the future can be determined, and the transaction unit value data of the three days in the future can be determined according to the historical transaction data, the real-time unit value data and the supply and demand information, and optionally, the unit value data of the three days in the future can be represented by a daily price curve. In the process of determining the value data of the transaction units, aggressive, conservative, stable and other prediction rules can be adopted to increase the diversity of the value data of the transaction units. Furthermore, the transaction result information corresponding to the object in the case of multiple transaction unit value data can be determined, and the transaction result information may include: trading revenue or trading loss risk information. The target transaction unit value data can be automatically determined from the transaction unit value data according to the transaction result information. Or, transaction result information corresponding to the value data of the multiple transaction units can be output to the user, so that the user can determine the target value data of the transaction units according to the output information.

The preset condition can be used for restricting the transaction result information. For example, the preset condition may be: the transaction income exceeds a preset income value; or sorting the transaction income information corresponding to the various transaction process information, wherein the sorting position corresponding to the target transaction process information is in the front, and the like.

In one example of the present application, it is assumed that summer is a power consumption peak period, and a short time of increase in power rate may occur in the power consumption peak period.

In view of the above situation, the embodiment of the application can help the user determine that the target transaction process information is met, so that the transaction result information meets the preset condition.

In view of the above situation, the embodiment of the present application may be configured to increase the time period of the unit value data according to a rule of the unit value data in the power consumption peak period. On the one hand, the resource can be prevented from being purchased in the increased time period, and the transaction loss risk is further reduced. On the other hand, the increased time period may be avoided, and the resources may be purchased in a time period other than the increased time period described above. In yet another aspect, where the existing resources are sufficient, the transfer of resources may be performed during the increase period.

In view of the above situation, the embodiments of the present application may allocate resource consumption information for determining the first transaction and the second transaction. Assume that the first transaction corresponds to a first weight and the second transaction corresponds to a second weight. The first weight may be increased and the second weight may be decreased during the increase period; and, during a non-increasing time period outside the increasing time period, the first weight may be decreased and the second weight may be increased. In the embodiment of the application, the first weight in the increased time period can be greater than the first weight in the non-increased time period, so that the allocation of the existing resources can be increased in the price rising time period of the electricity utilization peak period, the allocation of spot transactions is reduced, and the transaction cost can be reduced.

Optionally, the determining the prediction result of the resource consumption information specifically includes: determining historical resource consumption data corresponding to the use objects of at least one use object type; and predicting the resource consumption information of the use objects of the at least one kind of use objects in at least one time dimension according to the historical resource consumption data and the environment parameters of the use objects.

In addition to determining transaction information, embodiments of the present application may also perform other transaction processing.

Referring to fig. 6, an illustration of a power transaction process of an embodiment of the present application is shown. The electric power transaction processing specifically includes: basic information processing, electric quantity prediction decomposition, transaction auxiliary analysis and transaction result output.

Wherein, the basic information processing specifically comprises: qualification admission, electric power sale contract signing, transaction system registration and the like.

The electric quantity prediction decomposition may be configured to decompose a prediction result of the first time dimension into a second time dimension, and specifically includes: annual prediction, decomposition by month; monthly prediction and daily decomposition; day-ahead prediction, hourly decomposition, etc.

The transaction assistance analysis specifically includes: historical transaction analysis and future transaction prediction.

Historical transaction data can be obtained from a transaction system through historical transaction analysis, and the transaction data are imported according to time dimensions of days, weeks, months, years and the like; corresponding trading revenue may also be output.

The future transaction prediction may include: predicting the electric quantity; and prediction of trading revenue under different rules.

The transaction results may include: the transaction electric quantity, the transaction unit value data, the transaction varieties and the like can also comprise: the energy-saving power generation system aims to meet the requirements of reducing power consumption cost, optimizing energy structure, improving green environmental protection benefits and the like.

In summary, the resource processing method of the embodiment of the application can meet the accuracy requirements of acquisition, statistics and prediction of resource-related data in transaction, and provides effective basis for analysis and decision of transaction process information such as transaction unit value data in the transaction process.

In addition, the embodiment of the application can convert the change of the environmental parameter of the using object into the change of the prediction result of the resource consumption information, and provides a more accurate prediction result.

In addition, the embodiment of the application can track and capture real-time unit value data in real time, and determine transaction process information by using historical transaction data and the real-time unit value data. In this way, labor costs can be saved and transaction risks can be reduced to a certain extent.

Method example five

In one embodiment of the present application, service processing may also be performed.

Referring to fig. 7, a schematic diagram of a service process according to an embodiment of the present application is shown. The service can be a service related to resources, such as a carbon transaction, a virtual power plant, an auxiliary service, an energy right transaction, a green certificate transaction and the like. The new service can be an important carrier for realizing greening and flexibility on the electricity utilization structure.

In an embodiment of the present application, a processing result may also be displayed.

Referring to fig. 8, a schematic diagram of presentation data of an embodiment of the present application is shown. Wherein presenting the data may include: displaying electricity consumption data, transaction data and transaction results.

In this case, the electricity consumption data of the objects used in the corresponding region, such as electricity consumption data of bases in a national map, electricity consumption data of regions in a world map, and the like, may be displayed on the map.

The transaction data may include: trading electric quantity, trading variety, new service and the like.

Wherein the transaction amount may include: the total transaction electricity quantity of the year, the monthly transaction electricity quantity and the change condition of the historical annual transaction electricity quantity.

The transaction varieties may include: thermal power and new energy dimensionality; medium-long term, spot-shipment dimensions; bilateral, bid, listing dimensions; local and cross-regional dimensions; real-time curve display of spot transactions in a preset area and the like. The embodiment of the application can support the display of the transaction data corresponding to the transaction varieties with different dimensions.

The transaction result may be embodied in at least one of the following aspects: the power consumption cost is reduced, the energy structure is optimized, and the green and environment-friendly benefits are achieved. The embodiment of the application can display monthly or annual transaction data of the base to show the result of reducing the electricity consumption cost. The embodiment of the application can display the transaction data of thermal power, wind power, hydropower and other varieties in the base to explain the result of optimizing the energy structure. The embodiment of the application can display the transaction data of different bases in different time dimensions so as to show the result of green environmental protection benefits.

It should be noted that for simplicity of description, the method embodiments are described as a series of acts, but those skilled in the art should understand that the embodiments are not limited by the described order of acts, as some steps can be performed in other orders or simultaneously according to the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.

The embodiment of the application also provides a resource processing device.

Referring to fig. 9, a block diagram of a resource processing apparatus according to an embodiment of the present application is shown, which may specifically include the following modules:

a collecting module 901 for collecting resource cost data; the resource cost data includes at least one of: value data and transaction data;

a determining module 902, configured to determine resource cost data corresponding to a usage object of at least one usage object type according to the resource cost data.

Optionally, the usage object category includes at least one of the following:

region, city, garden, computer lab, booth, rack and equipment.

Optionally, the collection module 901 includes:

the first collection module is used for crawling resource cost data from a third-party platform; or alternatively

The second collection module is used for acquiring resource cost data from the financial data; or

And the third collection module is used for performing text recognition and semantic recognition on the files in the non-text format to obtain resource cost data.

Optionally, the determining module 902 includes:

a first determining module, configured to determine resource cost data corresponding to a usage object of a first usage object type; or

A second determining module, configured to determine resource cost data corresponding to the object of the second object type according to the resource cost data corresponding to the object of the first object type and the consumption parameter corresponding to the object of the second object type included in the first object type.

Optionally, the apparatus may further include:

a first providing module, configured to provide a query interface corresponding to the resource cost data for the at least one type of object.

Optionally, the apparatus may further include:

the operation data determining module is used for determining operation data corresponding to the use object of at least one kind of use object;

and the second providing module is used for providing a query interface corresponding to the running data.

Optionally, the apparatus may further include:

the historical resource consumption data determining module is used for determining historical resource consumption data corresponding to the use object of at least one use object type;

and the prediction module is used for predicting the resource consumption information of the use object of the at least one kind of use object in at least one time dimension according to the historical resource consumption data and the environment parameters of the use object.

Optionally, the environmental parameter may include at least one of the following:

physical environment parameters, lifecycle parameters, and shelving parameters of the object of use.

Optionally, the apparatus may further include:

and the transaction information determining module is used for determining the transaction information corresponding to the use object according to the resource cost data, the historical resource consumption data and the prediction result of the resource consumption information corresponding to the use object of at least one use object type.

Optionally, the transaction information determining module specifically includes:

the first transaction information determining module is used for determining distribution information between a first transaction and a second transaction corresponding to the use object; or alternatively

The second transaction information determining module is used for determining the information of the first transaction or the information of the second transaction corresponding to the using object; or alternatively

And the third transaction information determining module is used for determining the transaction result information respectively corresponding to the use objects under the condition of multiple kinds of transaction process information.

Optionally, the transaction information specifically includes at least one of the following:

supply and demand information, transaction process information and transaction result information.

Referring to fig. 10, a schematic structural diagram of an embodiment of a resource processing apparatus according to the present application is shown, which may specifically include the following modules: the system comprises a cost processing module, a transaction processing module, an operation data processing module, a service processing module and a display module.

The cost processing module can determine resource cost data corresponding to at least one type of use object, and provide a query interface corresponding to the resource cost data. The cost processing module may also be used to perform the process of FIG. 2, for example.

The transaction processing module is used to perform the transaction processing of fig. 6, for example. The service processing module is used to perform transaction processing such as that of fig. 7. A data processing module is run for performing the process of fig. 3, for example.

The presentation module may be used to perform the process of fig. 8, for example, to present data to a user, for example, query results for resource cost data may be presented to a user, real-time or historical operational data may be presented to a user, or historical or predicted transaction data may be presented to a user, etc.

Referring to fig. 11, a block diagram of a resource processing apparatus according to an embodiment of the present application is shown, which may specifically include the following modules:

a prediction result determining module 1101 configured to determine a prediction result of the resource consumption information;

the transaction information determining module 1102 is configured to determine transaction information corresponding to a usage object according to resource cost data, historical resource consumption data, and the prediction result corresponding to the usage object of at least one usage object type.

Optionally, the transaction information determining module 1102 specifically includes:

the first transaction information determining module is used for determining distribution information between a first transaction and a second transaction corresponding to the use object; or

And the third transaction information determining module is used for determining the transaction result information respectively corresponding to the using objects under the condition of various transaction process information.

Optionally, the prediction result determining module 1101 specifically includes:

and the prediction module is used for predicting the resource consumption information of the use object of the at least one kind of use object in at least one time dimension according to the historical resource consumption data and the environment parameter of the use object.

The embodiments in the present specification are all described in a progressive manner, and each embodiment focuses on differences from other embodiments, and portions that are the same and similar between the embodiments may be referred to each other.

With regard to the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be described in detail here.

Embodiments of the application can be implemented as a system or apparatus employing any suitable hardware and/or software for the desired configuration. Fig. 12 schematically illustrates an exemplary device 1500 that can be used to implement various embodiments described herein.

For one embodiment, fig. 12 illustrates an exemplary device 1500, which device 1500 may comprise: one or more processors 1502, a system control module (chipset) 1504 coupled with at least one of the processors 1502, system Memory 1506 coupled with the system control module 1504, non-volatile Memory (NVM) storage 1508 coupled with the system control module 1504, one or more input/output devices 1510 coupled with the system control module 1504, and a network interface 1512 coupled with the system control module 1506. The system memory 1506 may include: instructions 1562, the instructions 1562 may be executed by the one or more processors 1502.

The processor 1502 may include one or more single-core or multi-core processors, and the processor 1502 may include any combination of general-purpose processors or special-purpose processors (e.g., graphics processors, application processors, baseband processors, etc.). In some embodiments, the device 1500 can be a server, a target device, a wireless device, etc., as described in embodiments herein.

In some embodiments, the apparatus 1500 may include one or more machine-readable media (e.g., the system memory 1506 or the NVM/storage 1508) having instructions and one or more processors 1502 configured to execute the instructions to implement the modules included by the aforementioned means to perform the actions described in embodiments of the present application.

System control module 1504 for one embodiment may include any suitable interface controller to provide any suitable interface to at least one of processors 1502 and/or any suitable device or component in communication with system control module 1504.

System control module 1504 for one embodiment may include one or more memory controllers to provide an interface to system memory 1506. The memory controller may be a hardware module, a software module, and/or a firmware module.

System memory 1506 for one embodiment may be used to load and store data and/or instructions 1562. For one embodiment, system Memory 1506 may include any suitable volatile Memory, such as suitable DRAM (Dynamic Random Access Memory). In some embodiments, the system memory 1506 may include: double data rate type four synchronous dynamic random access memory (DDR 4 SDRAM).

System control module 1504 for one embodiment may include one or more input/output controllers to provide an interface to NVM/storage 1508 and input/output device(s) 1510.

NVM/storage 1508 for one embodiment may be used to store data and/or instructions 1582. NVM/storage 1508 may include any suitable non-volatile memory (e.g., flash memory, etc.) and/or may include any suitable non-volatile storage device(s), such as one or more Hard Disk Drive(s) (HDD (s)), one or more Compact Disc (CD) Drive(s), and/or one or more Digital Versatile Disc (DVD) Drive(s), etc.

NVM/storage 1508 may include storage resources that are physically part of the device on which apparatus 1500 is installed or that may be accessed by the device and not necessarily part of the device. For example, the NVM/storage 1508 may be accessible over a network via the network interface 1512 and/or through the input/output device 1510.

Input/output device(s) 1510 for one embodiment may provide an interface for device 1500 to communicate with any other suitable device, and input/output device(s) 1510 may include communication components, audio components, sensor components, and so forth.

Network interface 1512 for one embodiment may provide an interface for device 1500 to communicate with one or more networks and/or with any other suitable means, and device 1500 may communicate wirelessly with one or more components of a Wireless network according to any of one or more Wireless network standards and/or protocols, such as to access a Wireless network based on a communication standard, such as WiFi (Wireless Fidelity), 2G or 3G or 4G or 5G, or a combination thereof.

For one embodiment, at least one of the processors 1502 may be packaged together with logic for one or more controllers (e.g., memory controllers) of the system control module 1504. For one embodiment, at least one of the processors 1502 may be packaged together with logic for one or more controllers of the System control module 1504 to form a System In Package (SiP). For one embodiment, at least one of the processors 1502 may be integrated on the same initiative with the logic of one or more controllers of system control module 1504. For one embodiment, at least one of the processors 1502 may be integrated on the same Chip with logic for one or more controllers of the System control module 1504 to form a System on Chip (SoC).

In various embodiments, device 1500 may include, but is not limited to: a computing device such as a desktop computing device or a mobile computing device (e.g., a laptop computing device, a handheld computing device, a tablet, a netbook, etc.). In various embodiments, device 1500 may have more or fewer components and/or different architectures. For example, in some embodiments, device 1500 may include one or more cameras, keyboards, liquid Crystal Display (LCD) screens (including touch screen displays), non-volatile memory ports, multiple antennas, graphics chips, application Specific Integrated Circuits (ASICs), and speakers.

Wherein, if the display comprises a touch panel, the display screen may be implemented as a touch screen display to receive input signals from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

The present application also provides a non-transitory readable storage medium, where one or more modules (programs) are stored in the storage medium, and when the one or more modules are applied to an apparatus, the apparatus may be caused to execute instructions (instructions) of methods in the present application.

Provided in one example is an apparatus comprising: one or more processors; and, instructions in one or more machine-readable media stored thereon, which when executed by the one or more processors, cause the apparatus to perform a method as in embodiments of the present application, which may include: the method shown in any one of figures 1 to 8.

One or more machine-readable media are also provided in one example, having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform a method as in embodiments of the application, which may include: the method shown in any one of figures 1 to 8.

The specific manner in which each module performs operations of the apparatus in the above embodiments has been described in detail in the embodiments related to the method, and will not be described in detail here, and reference may be made to part of the description of the method embodiments for relevant points.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable resource processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable resource processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable resource processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable resource processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the true scope of the embodiments of the present application.

Finally, it should also be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one of 8230, and" comprising 8230does not exclude the presence of additional identical elements in a process, method, logistics object or apparatus comprising the element.

The foregoing detailed description has provided a resource processing method, a resource processing apparatus, a device, and a machine-readable medium, and the principles and embodiments of the present application have been described herein using specific examples, which are merely used to help understand the method and the core ideas of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A method for processing resources, the method comprising:

determining resource cost data corresponding to the use object of at least one use object type according to the resource cost data;

wherein the collecting resource cost data comprises: crawling resource cost data from a third party platform; or, obtaining resource cost data from the financial data; or performing text recognition and semantic recognition on the file in the non-text format to obtain resource cost data;

the determining resource cost data corresponding to the at least one usage object of the usage object category includes: determining resource cost data corresponding to the use object of the first use object type; alternatively, the resource cost data corresponding to the object to be used of the second object type is determined based on the resource cost data corresponding to the object to be used of the first object type and the consumption parameter corresponding to the object to be used of the second object type included in the first object type.

2. The method of claim 1, wherein the usage object category comprises at least one of:

region, city, garden, computer lab, booth, rack and equipment.

3. The method according to any one of claims 1 to 2, further comprising:

and aiming at the at least one type of the using object, providing a query interface corresponding to the resource cost data.

4. The method according to any one of claims 1 to 2, further comprising:

determining operation data corresponding to the use object of at least one use object type;

and providing a query interface corresponding to the running data.

5. The method according to any one of claims 1 to 2, further comprising:

determining historical resource consumption data corresponding to the use objects of at least one use object type;

and predicting the resource consumption information of the use objects of the at least one kind of use objects in at least one time dimension according to the historical resource consumption data and the environment parameters of the use objects.

6. The method of claim 5, wherein the environmental parameter comprises at least one of:

7. The method according to any one of claims 1 to 2, further comprising:

and determining transaction information corresponding to the use object according to the resource cost data, the historical resource consumption data and the prediction result of the resource consumption information corresponding to the use object of at least one use object type.

8. The method of claim 7, wherein the determining transaction information corresponding to the object of use comprises:

determining distribution information between a first transaction and a second transaction corresponding to the use object; or

Determining information of a first transaction or information of a second transaction corresponding to the using object; or

And determining transaction result information respectively corresponding to the using objects under the condition of various transaction process information.

9. The method of claim 7, wherein the transaction information comprises at least one of:

10. A method for processing resources, the method comprising:

determining a prediction result of the resource consumption information;

determining transaction information corresponding to the use object according to resource cost data, historical resource consumption data and the prediction result corresponding to the use object of at least one use object type;

wherein the determining the transaction information corresponding to the use object comprises: determining distribution information between a first transaction and a second transaction corresponding to the use object; or determining the information of the first transaction or the information of the second transaction corresponding to the use object; or determining the transaction result information respectively corresponding to the using objects under the condition of multiple transaction process information;

the determining the prediction result of the resource consumption information comprises:

and predicting resource consumption information of the use objects of the at least one use object type in at least one time dimension according to the historical resource consumption data and the environmental parameters of the use objects.

11. The method of claim 10, wherein the transaction information comprises at least one of:

12. An apparatus for resource handling, the apparatus comprising:

a collection module to collect resource cost data; the resource cost data includes at least one of: value data and transaction data;

a determining module, configured to determine resource cost data corresponding to a usage object of at least one usage object type according to the resource cost data;

wherein the collection module comprises:

the first collection module is used for crawling resource cost data from a third-party platform; or

The second collection module is used for acquiring resource cost data from the financial data; or alternatively

The third collection module is used for performing text recognition and semantic recognition on the files in the non-text format to obtain resource cost data;

the determining module comprises:

13. An apparatus for resource handling, the apparatus comprising:

the transaction information determining module is used for determining transaction information corresponding to the use object according to resource cost data, historical resource consumption data and the prediction result corresponding to the use object of at least one use object type;

wherein the transaction information determination module comprises:

The second transaction information determining module is used for determining the information of the first transaction or the information of the second transaction corresponding to the using object; or

The third transaction information determining module is used for determining transaction result information respectively corresponding to the using objects under the condition of various transaction process information;

the prediction result determination module includes:

14. A resource processing device, comprising:

one or more processors; and

one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the resource processing device to perform the method recited by one or more of claims 1-9.

15. One or more machine-readable media having instructions stored thereon, which when executed by one or more processors perform the method recited by one or more of claims 1-9.

16. A resource processing device, comprising:

one or more processors; and

one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the resource processing device to perform the method of one or more of claims 10-11.

17. One or more machine-readable media having instructions stored thereon, which when executed by one or more processors perform the method recited by one or more of claims 10-11.