Multi-dimensional risk identification and early warning method and system for electricity market

Abstract

The invention discloses a multi-dimensional risk identification and early warning method and system for an electricity market, and belongs to the technical field of multi-dimensional risk identification and early warning. After a processing terminal is triggered, a customer account is constructed according to a login message; constructing a starting customer attribute table, and constructing a multi-dimensional credit evaluation index of the electricity market after one-time denoising; constructing automatic attributes of customers; constructing information obtained by monitoring the query information; constructing customer affiliated attributes, inputting the customer affiliated attributes into an attribute balance estimation mode, and constructing balance identification codes associated with the attributes; multi-dimensional credit evaluation indexes of the electric power market after denoising are constructed, denoising control is executed according to the loop values and the traceability reconstruction nodes, and the performance and task functions of an energy interconnection subject credit evaluation mode constructed by the digital electric power market are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of multi-dimensional risk identification and early warning, and specifically relates to a multi-dimensional risk identification and early warning method and system for an electricity market. Background Art

[0002] The electricity market is a natural monopoly market. Since the power grid is an infrastructure, in order to prevent the waste of resources caused by duplicate construction, the transmission network is usually allowed to operate in a monopoly and give full play to its natural monopoly potential. However, due to the monopoly position of the power grid, the power grid company has sufficient market power to carry out vertical integration mergers upstream (power generation side) and downstream (power sales side), thereby further expanding its monopoly position.

[0003] In terms of the multi-dimensional credit evaluation indicators of the electricity market, as mentioned in the prior art solution with patent publication number "CN114663219B", a credit evaluation model for energy interconnection entities is constructed based on the multi-dimensional credit evaluation indicators of the electricity market.

[0004] Before constructing the credit assessment model of energy interconnection subject, it is necessary to denoise the multi-dimensional credit assessment indicators of the electricity market, and then construct the credit assessment model of energy interconnection subject based on the denoised multi-dimensional credit assessment indicators of the electricity market. The current denoising method for the multi-dimensional credit assessment indicators of the electricity market has the defects of denoising the multi-dimensional credit assessment indicators by relying on unique attributes, and it is not easy to correctly and effectively denoise the customer's proprietary requirements and the multi-dimensional credit assessment indicators of the electricity market, which makes the multi-dimensional credit assessment indicators of the electricity market after denoising incorrect and lack of warning, and is not suitable for constructing the performance and customer experience of the energy interconnection subject credit assessment model.

[0005] Invention Information

[0006] In order to solve the defects in the prior art, the present invention proposes a multi-dimensional risk identification and early warning system and method for the power market, which overcomes the defects of the existing multi-dimensional credit evaluation indicator denoising of the power market, that is, the multi-dimensional credit evaluation indicator denoising is performed by relying on unique attributes, and it is not easy to correctly and effectively denoise the proprietary requirements of customers and the multi-dimensional credit evaluation indicators of the power market. In this way, the multi-dimensional credit evaluation indicators of the power market after denoising are incorrect, lack early warning, and are not suitable for constructing the performance and customer experience of the credit evaluation model of the energy interconnection subject, thereby achieving the advantage of improving the performance and task function of the digital power market to construct the credit evaluation model of the energy interconnection subject.

[0007] The present invention uses the following technical solutions.

[0008] A multi-dimensional risk identification and early warning method for the power market, running on a processing terminal, includes:

[0009] De-noising the multi-dimensional credit evaluation indicators of the power market, and then constructing the energy interconnection subject credit evaluation model based on the denoised multi-dimensional credit evaluation indicators of the power market;

[0010] The method for denoising the multi-dimensional credit assessment indicators of the power market includes:

[0011] After the processing terminal is triggered, the customer account is constructed according to the login message;

[0012] Starting a value collection program to collect customer input information, parsing the input information, and constructing an initial customer attribute table;

[0013] The initial customer attribute table is used as standard denoising information to perform denoising of the multi-dimensional credit evaluation index of the power market, and a multi-dimensional credit evaluation index of the power market after denoising is constructed.

[0014] A multi-dimensional risk identification and early warning system for the power market, comprising:

[0015] A customer account construction module, used to construct a customer account according to a login message after the processing terminal is triggered, wherein the customer account is provided with a customer's initial review reconstruction frequency identification code;

[0016] A multi-dimensional credit evaluation index construction module for a de-noised power market is used to start a numerical collection program to collect customer input information, parse the input information, construct an initial customer attribute table, use the initial customer attribute table as standard de-noised information, perform de-noising of the multi-dimensional credit evaluation index of the power market, and construct a multi-dimensional credit evaluation index of the power market after de-noising. Here, the multi-dimensional credit evaluation index of the power market after de-noising is a professional introduction to the multi-dimensional credit evaluation index of the power market after de-noising;

[0017] The customer automatic attribute construction module is used to perform response detection on the customer, construct the customer's automatic response detection, use the automatic response detection to refresh the initial customer attribute table, and construct the customer's automatic attributes.

[0018] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0019] After the processing terminal is triggered, a customer account is constructed according to the login message; an initial customer attribute table is constructed, and a multi-dimensional credit evaluation index of the power market after a de-noising is constructed; customer automatic attributes are constructed; information obtained by query information monitoring is constructed; customer ancillary attributes are constructed and entered into the attribute balance estimation model, and a balance identification code associated with each attribute is constructed; a multi-dimensional credit evaluation index of the power market after a second de-noising is constructed, and de-noising control is performed based on the cycle value and the traceability reconstruction node, which overcomes the existing multi-dimensional credit evaluation index denoising of the power market, which relies on unique attributes to perform multi-dimensional credit evaluation index denoising, and is not easy to correctly and effectively denoise the proprietary requirements of customers and the multi-dimensional credit evaluation index of the power market, so that the multi-dimensional credit evaluation index of the power market after de-noising is incorrect, lacks early warning, and is not suitable for constructing the performance and customer experience of the energy interconnection subject credit evaluation model, thereby achieving the advantages of improving the performance and task functions of the energy interconnection subject credit evaluation model constructed by the digital power market. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a partial flow chart of the multi-dimensional risk identification and early warning method of the power market described in the present invention;

[0021] Figure 2 It is a partial structural diagram of the multi-dimensional risk identification and early warning system for the power market described in the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely expressed in combination with the drawings in the embodiments of the present invention. The embodiments expressed in this application are only some embodiments of the present invention, not all embodiments. According to the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the protection scope of the present invention.

[0023] like Figure 1 As shown, a multi-dimensional risk identification and early warning method for the power market according to the present invention runs on a processing terminal and includes:

[0024] De-noising is performed on the multi-dimensional credit evaluation indicators of the electricity market, and then a credit evaluation model for energy interconnection entities is constructed based on the multi-dimensional credit evaluation indicators of the electricity market after denoising; the processing terminal can be a computer.

[0025] The method for denoising the multi-dimensional credit assessment indicators of the power market includes:

[0026] After the processing terminal is triggered, the customer account is constructed according to the login message;

[0027] In a preferred but non-limiting embodiment of the present invention, the customer account is provided with a customer's initial review reconstruction frequency identification code.

[0028] Starting a value collection program to collect customer input information, parsing the input information, and constructing an initial customer attribute table;

[0029] The initial customer attribute table is used as standard denoising information to perform denoising of the multi-dimensional credit evaluation index of the power market, and a multi-dimensional credit evaluation index of the power market after denoising is constructed.

[0030] In a preferred but non-limiting embodiment of the present invention, the multi-dimensional credit evaluation index of the electricity market after de-noising is the multi-dimensional credit evaluation index of the electricity market after de-noising using a K-means algorithm.

[0031] In a preferred but non-limiting embodiment of the present invention, the method for performing denoising on the multi-dimensional credit assessment index of the power market further includes:

[0032] Perform response detection on the customer, construct automatic response detection of the customer, use the automatic response detection to refresh the initial customer attribute table, and construct customer automatic attributes; trigger the behavior listening component, use the behavior listening component to perform customer query information listening, and construct information obtained by query information listening; use the information obtained by query information listening to construct customer ancillary attributes, enter the customer automatic attributes and customer ancillary attributes into the attribute balance estimation model, and construct a balance identification code associated with each attribute; perform multi-dimensional credit evaluation index denoising of the power market based on the balance identification code, customer automatic attributes, and customer ancillary attributes, construct a multi-dimensional credit evaluation index of the power market after denoising again, perform customer mobile detection based on the multi-dimensional credit evaluation index of the power market after denoising again, use the mobile detection value to execute the multi-dimensional credit evaluation index cycle of the power market after denoising again, and use the initial review reconstruction frequency identification code to construct a traceability reconstruction node, and perform denoising control based on the cycle value and the traceability reconstruction node.

[0033] In a preferred but non-limiting embodiment of the present invention, the cycle value is a multi-dimensional credit evaluation indicator of the power market after motor information denoising.

[0034] In a preferred but non-limiting embodiment of the present invention, the method of performing denoising control based on loop values ​​and traceability reconstruction nodes specifically includes: detecting node triggering of the traceability reconstruction node and constructing a trigger response coefficient; constructing a customer behavior training model, taking the intercepted customer behavior information as point-in-time input information, performing customer behavior estimation based on the behavior training model, and constructing a behavior estimation value; allocating a response refresh queue with the behavior estimation value, performing a node loop of the traceability reconstruction node based on the response refresh queue and the trigger response coefficient, and performing denoising control with the node loop value.

[0035] In a preferred but non-limiting embodiment of the present invention, the method of using the behavior listening component to perform customer query information listening and constructing the information obtained by query information listening specifically includes: obtaining the customer's access interface, and determining whether the retention time of the access interface meets the pre-defined time critical amount; if the retention time meets the pre-defined time critical amount, registering the access interface as the reference interface; performing interface information identification on the access interface, and using the interface information identification value to construct additional listening information one; obtaining the access sub-area of ​​the access interface, using the reference interface as the interface base point, and constructing additional listening information two according to the triggered order of the access sub-area; constructing the query information listening information according to the additional listening information one, the additional listening information two and the retention time.

[0036] In a preferred but non-limiting embodiment of the present invention, the method for constructing the information obtained by query information listening based on the information one obtained by additional listening, the information two obtained by additional listening and the retention time specifically includes: extracting the area information of the access sub-area of ​​the information two obtained by additional listening, and registering the triggering time of the access sub-area; constructing the standard area listening attribute based on the area information and the triggering time; starting the attribute distribution importance of the information one obtained by additional listening and the triggered order of the information two obtained by additional listening, and generating a time segmentation focus coefficient based on the attribute distribution importance and the triggered order; after segmenting the retention time according to the time segmentation focus coefficient, executing the standard area listening attribute revision to form the information obtained by query information listening.

[0037] In a preferred but non-limiting embodiment of the present invention, the method of denoising the multidimensional credit evaluation indicators of the electricity market based on the balance identification code, customer automatic attributes, and customer subsidiary attributes, and constructing the multidimensional credit evaluation indicators of the electricity market after denoising again, specifically includes: constructing a market information table, the market information table has an information reliability identification code, and the information reliability identification code is constructed through the time point shrinkage coefficient, the source of information, and the completeness of information; after constructing the joint denoising attributes with the balance identification code, customer automatic attributes, and customer subsidiary attributes, performing adaptive denoising on the market information table based on the reliable identification code, and using the multidimensional credit evaluation indicators of the electricity market after adaptive denoising to construct the multidimensional credit evaluation indicators of the electricity market after denoising again.

[0038] In a preferred but non-limiting embodiment of the present invention, the method of entering the customer automatic attributes and customer subsidiary attributes into the attribute balance estimation mode and constructing a balance identification code associated with each attribute specifically includes: starting an information volume analysis program of the attribute balance estimation mode, using the information volume analysis program to perform information volume ratio analysis of the customer automatic attributes and customer subsidiary attributes, and using the information volume ratio analysis value to construct a balance coefficient one; starting a main-subsidiary analysis program of the attribute balance estimation mode, performing attribute margin estimation of the customer automatic attributes and the customer subsidiary attributes respectively according to the main-subsidiary analysis program, and constructing a balance coefficient two with an automatic-subsidiary identification code according to the attribute margin estimation value; starting the attribute analysis program of the attribute balance estimation mode, performing attribute analysis of the customer automatic attributes and the customer subsidiary attributes according to the attribute analysis program, and constructing a balance coefficient three; constructing a balance identification code associated with each attribute according to the balance coefficient one, balance coefficient two, and balance coefficient three.

[0039] In a preferred but non-limiting embodiment of the present invention, a method for denoising a multi-dimensional credit assessment index of an electricity market provided in combination with mobile information specifically includes: determining whether the multi-dimensional credit assessment index of the electricity market after denoising meets a pre-defined denoising critical value; if it does not meet the pre-defined denoising critical value, generating an early warning command; using the early warning command to execute additional information sampling of the customer, to reconstruct the multi-dimensional credit assessment index of the electricity market after denoising using the additional information collection value.

[0040] like Figure 2 As shown, the multi-dimensional risk identification and early warning system of the power market described in the present invention includes:

[0041] A customer account construction module, used to construct a customer account according to a login message after the processing terminal is triggered, wherein the customer account is provided with a customer's initial review reconstruction frequency identification code;

[0042] A multi-dimensional credit evaluation index construction module for a de-noised power market is used to start a numerical collection program to collect customer input information, parse the input information, construct an initial customer attribute table, use the initial customer attribute table as standard de-noised information, perform de-noising of the multi-dimensional credit evaluation index of the power market, and construct a multi-dimensional credit evaluation index of the power market after de-noising. Here, the multi-dimensional credit evaluation index of the power market after de-noising is a professional introduction to the multi-dimensional credit evaluation index of the power market after de-noising;

[0043] The customer automatic attribute construction module is used to perform response detection on the customer, construct the customer's automatic response detection, use the automatic response detection to refresh the initial customer attribute table, and construct the customer's automatic attributes.

[0044] In a preferred but non-limiting embodiment of the present invention, the multi-dimensional risk identification and early warning system for the power market further includes:

[0045] The information construction module obtained by query information interception is used to trigger the behavior interception component, use the behavior interception component to execute the query information interception of the customer, and construct the information obtained by the query information interception; the balance identification code construction module is used to construct the customer's attached attributes with the information obtained by the query information interception, enter the customer's automatic attributes and the customer's attached attributes into the attribute balance estimation mode, and construct the balance identification code associated with each attribute; the multi-dimensional credit evaluation index construction module of the power market after re-denoising is used to perform multi-dimensional credit evaluation index denoising of the power market according to the balance identification code, the customer's automatic attributes, and the customer's attached attributes, construct the multi-dimensional credit evaluation index of the power market after re-denoising, perform customer mobile detection according to the multi-dimensional credit evaluation index of the power market after re-denoising, use the mobile detection value to execute the multi-dimensional credit evaluation index cycle of the power market after re-denoising, and use the starting review reconstruction frequency identification code to construct the traceability reconstruction node, and perform denoising control according to the cycle value and the traceability reconstruction node, and the cycle value is the multi-dimensional credit evaluation index of the power market after mobile information denoising.

[0046] The beneficial effects of the present invention are that, compared with the prior art, the technical effects of the present invention include:

[0047] After the processing terminal is triggered, a customer account is constructed according to the login message; an initial customer attribute table is constructed, and a multi-dimensional credit evaluation index of the power market after a de-noising is constructed; customer automatic attributes are constructed; information obtained by query information monitoring is constructed; customer ancillary attributes are constructed and entered into the attribute balance estimation model, and a balance identification code associated with each attribute is constructed; a multi-dimensional credit evaluation index of the power market after a second de-noising is constructed, and de-noising control is performed based on the cycle value and the traceability reconstruction node, which overcomes the existing multi-dimensional credit evaluation index denoising of the power market, which relies on unique attributes to perform multi-dimensional credit evaluation index denoising, and is not easy to correctly and effectively denoise the proprietary requirements of customers and the multi-dimensional credit evaluation index of the power market, so that the multi-dimensional credit evaluation index of the power market after de-noising is incorrect, lacks early warning, and is not suitable for constructing the performance and customer experience of the energy interconnection subject credit evaluation model, thereby achieving the advantages of improving the performance and task functions of the energy interconnection subject credit evaluation model constructed by the digital power market.

[0048] The present disclosure can be a system, method and / or computer program product. The computer program product can include a computer-readable backup medium carrying computer-readable program instructions for causing a processor to implement various aspects of the disclosure.

[0049] The computer readable backup medium can be a tangible network capable of retaining and backing up the instructions used by the instruction execution network. The computer readable backup medium can be, but is not limited to, an electrical backup network, a magnetic backup network, an optical backup network, an electromagnetic backup network, a semiconductor backup network, or any suitable combination of the above. Further examples of computer readable backup media (non-exhaustive list) include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (HD-ROM), digital versatile disk (DXD), memory stick, floppy disk, mechanically encoded network, such as punch cards or protrusions in grooves with instructions backed up thereon, and any suitable combination of the above. The computer readable backup medium used herein is not to be construed as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a power line cable), or an electrical signal transmitted through wires.

[0050] The computer readable program instructions expressed herein can be downloaded from the computer readable backup medium to each inference / processing power grid line, or downloaded to an external computer or external backup power grid line through a wireless network, such as the Internet, a local area network, a wide area network and / or a wireless network. The wireless network can include copper transmission cables, power transmission lines, wireless transmission, routers, firewalls, switches, gateway computers and / or edge service devices. The wireless network adapter card or wireless network interface in each inference / processing power grid line receives the computer readable program instructions from the wireless network and forwards the computer readable program instructions for storage in the computer readable backup medium in each inference / processing power grid line.

[0051] The computer program instructions for performing the operations of the present disclosure can be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, conditional setting values, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Sdaletal A, H++, etc., and ordinary procedural programming languages ​​such as "H" language or similar programming languages. The computer-readable program instructions can be executed completely on the client computer, partially on the client computer, as a separate software package, partially on the client computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the client computer through any other wireless network, including a local area network (LAb) or a wide area network (WAb), or can be connected to an external computer (just like using an Internet service provider to connect through the Internet). In some embodiments, the electronic circuit is customized by using the status values ​​of computer-readable program instructions, such as a programmable logic circuit, a field programmable gate array (FPGA) or a programmable logic array (PLA), and the electronic circuit can execute computer-readable program instructions to achieve various aspects of the overhead disclosure.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not deviate from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A multi-dimensional risk identification and early warning method for the power market, characterized in that: Runs on the processing terminal, including: De-noising the multi-dimensional credit evaluation indicators of the power market, and then constructing the energy interconnection subject credit evaluation model based on the denoised multi-dimensional credit evaluation indicators of the power market; The method for denoising the multi-dimensional credit assessment indicators of the power market includes: After the processing terminal is triggered, the customer account is constructed according to the login message; Starting a value collection program to collect customer input information, parsing the input information, and constructing an initial customer attribute table; The initial customer attribute table is used as standard denoising information to perform denoising of the multi-dimensional credit evaluation index of the power market, and a multi-dimensional credit evaluation index of the power market after denoising is constructed.

2. The multi-dimensional risk identification and early warning method for the power market according to claim 1 is characterized in that: The customer account is provided with the customer's initial review reconstruction frequency identification code.

3. The multi-dimensional risk identification and early warning method for the power market according to claim 2 is characterized in that: The multi-dimensional credit evaluation index of the electricity market after de-noising is the multi-dimensional credit evaluation index of the electricity market after de-noising using the K-means algorithm.

4. The multi-dimensional risk identification and early warning method for the power market according to claim 3 is characterized in that: The method for performing denoising on the multi-dimensional credit assessment index of the power market also includes: Perform response detection on the customer, construct automatic response detection of the customer, use the automatic response detection to refresh the initial customer attribute table, and construct customer automatic attributes; trigger the behavior listening component, use the behavior listening component to perform customer query information listening, and construct information obtained by query information listening; use the information obtained by query information listening to construct customer ancillary attributes, enter the customer automatic attributes and customer ancillary attributes into the attribute balance estimation model, and construct a balance identification code associated with each attribute; perform multi-dimensional credit evaluation index denoising of the power market based on the balance identification code, customer automatic attributes, and customer ancillary attributes, construct a multi-dimensional credit evaluation index of the power market after denoising again, perform customer mobile detection based on the multi-dimensional credit evaluation index of the power market after denoising again, use the mobile detection value to execute the multi-dimensional credit evaluation index cycle of the power market after denoising again, and use the initial review reconstruction frequency identification code to construct a traceability reconstruction node, and perform denoising control based on the cycle value and the traceability reconstruction node.

5. The multi-dimensional risk identification and early warning method for the power market according to claim 4 is characterized in that: The cycle value is a multi-dimensional credit evaluation indicator of the power market after the motor information is denoised.

6. The multi-dimensional risk identification and early warning method for the power market according to claim 5 is characterized in that: The method for performing denoising control based on the cycle value and the traceability reconstruction node specifically includes: detecting the node trigger of the traceability reconstruction node and constructing a trigger response coefficient; constructing a customer behavior training model, taking the intercepted customer behavior information as the time point input information, performing customer behavior estimation according to the behavior training model, and constructing a behavior estimation value; allocating a response refresh queue with the behavior estimation value, performing a node cycle of the traceability reconstruction node according to the response refresh queue and the trigger response coefficient, and performing denoising control with the node cycle value; The method of using the behavior listening component to perform customer query information listening and constructing the information obtained by query information listening specifically includes: obtaining the customer's access interface, determining whether the retention time of the access interface meets the pre-defined time threshold; if the retention time meets the pre-defined time threshold, registering the access interface as the reference interface; performing interface information identification on the access interface, and constructing additional listening information one using the interface information identification value; obtaining the access sub-area of ​​the access interface, using the reference interface as the interface base point, and constructing additional listening information two according to the triggered order of the access sub-area; constructing the query information listening information based on the additional listening information one, the additional listening information two and the retention time.

7. The multi-dimensional risk identification and early warning method for the power market according to claim 6 is characterized in that: The method for constructing the information obtained by query information listening based on the information one obtained by additional listening, the information two obtained by additional listening and the retention time specifically includes: extracting the area information of the access sub-area of ​​the information two obtained by additional listening, and registering the triggering time of the access sub-area; constructing the standard area listening attribute based on the area information and the triggering time; starting the attribute distribution importance of the information one obtained by additional listening and the triggered order of the information two obtained by additional listening, and generating the time segmentation focus coefficient based on the attribute distribution importance and the triggered order; after segmenting the retention time according to the time segmentation focus coefficient, executing the standard area listening attribute revision to form the information obtained by query information listening.

8. The multi-dimensional risk identification and early warning method for the power market according to claim 7 is characterized in that: The method of performing denoising of the multi-dimensional credit evaluation index of the power market according to the balance identification code, the customer automatic attribute, and the customer attached attribute, and constructing the multi-dimensional credit evaluation index of the power market after denoising again, specifically includes: constructing a market information table, the market information table has an information reliability identification code, and the information reliability identification code is constructed through the time point shrinkage coefficient, the information source, and the information completeness; after constructing the joint denoising attribute with the balance identification code, the customer automatic attribute, and the customer attached attribute, performing adaptive denoising on the market information table according to the reliable identification code, and constructing the multi-dimensional credit evaluation index of the power market after denoising again with the multi-dimensional credit evaluation index of the power market after adaptive denoising; The method of entering the customer automatic attributes and customer subsidiary attributes into the attribute balance estimation mode and constructing a balance identification code associated with each attribute specifically includes: starting an information volume analysis program of the attribute balance estimation mode, using the information volume analysis program to perform information volume ratio analysis of the customer automatic attributes and customer subsidiary attributes, and using the information volume ratio analysis value to construct a balance coefficient one; starting a main subsidiary analysis program of the attribute balance estimation mode, performing attribute margin estimation of the customer automatic attributes and the customer subsidiary attributes respectively according to the main subsidiary analysis program, and constructing a balance coefficient two with an automatic-subsidiary identification code according to the attribute margin estimation value; starting an attribute analysis program of the attribute balance estimation mode, performing attribute analysis of the customer automatic attributes and the customer subsidiary attributes according to the attribute analysis program, and constructing a balance coefficient three; constructing a balance identification code associated with each attribute according to the balance coefficient one, the balance coefficient two, and the balance coefficient three; The method for denoising the multi-dimensional credit assessment index of the power market given by the mobile information specifically includes: determining whether the multi-dimensional credit assessment index of the power market after denoising meets the pre-defined denoising critical value; if it does not meet the pre-defined denoising critical value, generating an early warning command; using the early warning command to execute additional information sampling of the customer, to reconstruct the multi-dimensional credit assessment index of the power market after denoising by using the additional information collection value.

9. A multi-dimensional risk identification and early warning system for the power market, characterized in that: include: A customer account construction module, used to construct a customer account according to a login message after the processing terminal is triggered, wherein the customer account is provided with a customer's initial review reconstruction frequency identification code; A multi-dimensional credit evaluation index construction module for a de-noised power market is used to start a numerical collection program to collect customer input information, parse the input information, construct an initial customer attribute table, use the initial customer attribute table as standard de-noised information, perform de-noising of the multi-dimensional credit evaluation index of the power market, and construct a multi-dimensional credit evaluation index of the power market after de-noising. Here, the multi-dimensional credit evaluation index of the power market after de-noising is a professional introduction to the multi-dimensional credit evaluation index of the power market after de-noising; The customer automatic attribute construction module is used to perform response detection on the customer, construct the customer's automatic response detection, use the automatic response detection to refresh the initial customer attribute table, and construct the customer's automatic attributes.

10. The multi-dimensional risk identification and early warning system for the power market according to claim 9 is characterized in that: The multi-dimensional risk identification and early warning system for the power market also includes: The information construction module obtained by query information interception is used to trigger the behavior interception component, use the behavior interception component to execute the query information interception of the customer, and construct the information obtained by the query information interception; the balance identification code construction module is used to construct the customer's attached attributes with the information obtained by the query information interception, enter the customer's automatic attributes and the customer's attached attributes into the attribute balance estimation mode, and construct the balance identification code associated with each attribute; the multi-dimensional credit evaluation index construction module of the power market after re-denoising is used to perform multi-dimensional credit evaluation index denoising of the power market according to the balance identification code, the customer's automatic attributes, and the customer's attached attributes, construct the multi-dimensional credit evaluation index of the power market after re-denoising, perform customer mobile detection according to the multi-dimensional credit evaluation index of the power market after re-denoising, use the mobile detection value to execute the multi-dimensional credit evaluation index cycle of the power market after re-denoising, and use the starting review reconstruction frequency identification code to construct the traceability reconstruction node, and perform denoising control according to the cycle value and the traceability reconstruction node, and the cycle value is the multi-dimensional credit evaluation index of the power market after mobile information denoising.

Images