CN110910009B - Power consumer management method and device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to a power consumer management method, a power consumer management device, computer equipment and a storage medium. The method comprises the following steps: acquiring power utilization behavior information and external credit information of a power consumer; carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information; carrying out deep analysis on the power utilization behavior information and the external credit investigation information after the standardization processing, and establishing a characteristic project of the payment characteristics of the power consumer; establishing a user fee urging scoring model based on the characteristic engineering of the payment characteristics of the power users; the power users are scored by adopting the user fee-prompting scoring model, corresponding fee-prompting strategies are called according to scoring results, the user fee-prompting scoring model of the power users is established based on the electricity utilization behavior information and the external credit information, then the power users are scored by utilizing the user fee-prompting scoring model, corresponding fee-prompting strategies are adopted for the power users according to the scoring results, and therefore the power users are managed quickly and effectively, and the users in a management shop are overall planned.
Description
Technical Field
The present application relates to the field of power consumer management technologies, and in particular, to a power consumer management method and apparatus, a computer device, and a storage medium.
Background
With the gradual slowing of the growth speed of social economy, the descending pressure of economy is gradually increased, and the recovery pressure of electric charges is increased day by day. In the face of different types of power users in the society, the power supplier can only take prevention and control measures to the whole of a certain type of power users for risk management, and the risk management cannot be quantized or grouped. In addition, in order to complete the electric charge recovery task, monthly fee-urging workload accounts for about half of the total workload, which causes serious influence on the propulsion of other services and has low working efficiency.
At present, the adopted fee urging method still stays in the original inherent mode, such as unified expiration urging, unified expiration power failure and the like, although the method is standard, the method is not the optimal fee urging method, for example, for some power consumers, no matter how the staff urge the fee, the fee is paid at a certain fixed time; some power consumers always pay and record good sudden arrearages; some power consumers are stubborn defaulting power consumers, no matter how the power consumers are charged, the situation that the power failure is not paid is not reached, and different reasons exist behind behaviors of each power consumer, so that in the implementation process, the inventor finds that at least the following problems exist in the traditional technology: the traditional technology cannot effectively and comprehensively manage power users.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a power consumer management method, apparatus, computer device, and storage medium capable of reasonably managing power consumers in view of the above technical problems.
A power consumer management method comprising the steps of:
acquiring power utilization behavior information and external credit information of a power consumer; the electricity consumption behavior information comprises business expansion information, appeal information, arrearage information and default electricity consumption information; the external credit investigation information comprises legal litigation information, court announcement information and information of the person who loses credit to be executed;
carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information;
carrying out deep analysis on the power utilization behavior information and the external credit investigation information after the standardization processing, and establishing a characteristic project of the payment characteristic of the power consumer;
establishing a user fee urging scoring model based on the payment characteristics of the power users;
and grading the power users by adopting a user fee-prompting grading model, and calling a corresponding fee-prompting strategy according to a grading result.
In one embodiment, the step of standardizing the power consumption behavior information and the external credit information includes the steps of:
respectively identifying a corresponding maximum attribute value and a corresponding minimum attribute value in the electricity utilization behavior information and the external credit information;
and correspondingly and respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner based on each maximum attribute value and each minimum attribute value.
In one embodiment, the user charge prompting scoring model comprises an electric charge default coefficient model, an arrearage frequency model, an electric charge defaulting coefficient model and a charge prompting sensitivity coefficient model.
In one embodiment, the electric charge default coefficient model is obtained based on the following formula:
wherein D represents an electric charge default coefficient model; r represents that the user default fund should be collected; n represents the total number of power consumers; l represents the interval between the month which produced the default gold most recently and the current month;
obtaining an arrearage frequency model based on the following formula:
where a represents an arrearage frequency model.
In one embodiment, the electric charge delinquent coefficient model is obtained based on the following formula:
wherein Q represents an electric charge delinquent coefficient model; n represents the total number of power consumers; p represents a payment date; d represents the electricity charge issuing date; n represents the number of times of the common owing fee;
acquiring a sensitivity coefficient model of hastening harvest based on the following formula:
wherein C represents a catalyst trapping sensitivity coefficient model; d 1 Represents the current month; d 2 Indicating the household date.
In one embodiment, in the step of performing deep analysis on the standardized power consumption behavior information and the standardized external credit investigation information to establish the feature engineering of the payment feature of the power consumer, the method for establishing the feature engineering includes one or any combination of the following methods: a timestamp processing method, a category attribute decomposition method, a binning/partitioning method, a cross feature method, a feature selection method, a feature scaling method, and a feature extraction method.
A power consumer management device comprising:
the information acquisition module is used for acquiring power utilization behavior information and external credit investigation information of a power consumer; the electricity consumption behavior information comprises business expansion information, appeal information, arrearage information and default electricity consumption information; the external credit investigation information comprises legal litigation information, court announcement information and information of the person who loses credit to be executed;
the standardized processing module is used for carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information;
the characteristic engineering extraction module is used for carrying out deep analysis on the power consumption behavior information and the external credit investigation information after the standardization processing, and establishing a characteristic engineering of the payment characteristics of the power consumer;
the model establishing module is used for establishing a user fee urging scoring model based on the characteristic engineering of the payment characteristics of the power users;
and the strategy calling module is used for grading the power users by adopting a user fee-prompting grading model and calling corresponding fee-prompting strategies according to grading results.
In one embodiment, the normalization processing module comprises:
the attribute value identification unit is used for respectively identifying a corresponding maximum attribute value and a corresponding minimum attribute value in the power utilization behavior information and the external credit information;
and the mapping unit is used for respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner correspondingly based on each maximum attribute value and each minimum attribute value.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the method when the processor executes the computer program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
One of the above technical solutions has the following advantages and beneficial effects:
the power consumer management method provided by each embodiment of the application comprises the following steps: acquiring power utilization behavior information and external credit investigation information of a power consumer; carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information; carrying out deep analysis on the standardized power utilization behavior information and the external credit investigation information, and extracting the payment characteristics of the power consumers; establishing a user fee urging scoring model based on the payment characteristics of the power users; the method comprises the steps of adopting a user fee-urging scoring model to score power users, calling corresponding fee-urging strategies according to scoring results, achieving the purpose that the user fee-urging scoring model of the power users is established based on power utilization behavior information and external credit information, then utilizing the user fee-urging scoring model to score payment behaviors of the power users, and adopting the corresponding fee-urging strategies for the power users according to the scoring results, thereby achieving the purpose of rapidly and effectively managing the power users based on a big data technology and comprehensively managing the users in a store.
Drawings
FIG. 1 is a flow diagram illustrating a method for power consumer management in one embodiment;
FIG. 2 is a schematic flow chart of the normalization process steps in one embodiment;
FIG. 3 is a block diagram of a power consumer management device in one embodiment;
FIG. 4 is a diagram of the internal structure of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In order to solve the problem that the conventional technology cannot effectively and comprehensively manage the power consumers, in one embodiment, as shown in fig. 1, a power consumer management method is provided, which includes the following steps:
step S110, acquiring power utilization behavior information and external credit investigation information of a power consumer; the electricity consumption behavior information comprises business expansion information, appeal information, arrearage information and default electricity consumption information; the external credit investigation information includes legal action information, court announcement information, and information on the person who loses credit being performed.
It should be noted that the present application is implemented based on a big data technology, and in an example, the method steps of the present application may be implemented by using spark technology or hadoop technology. The big data platform can provide the storage capacity of basic data and strong data processing capacity.
The electricity consumption behavior information refers to business expansion information, appeal information, arrearage information, default electricity consumption information and the like, and can be obtained from a power grid marketing system; the external credit investigation information refers to information such as legal action information, court announcement information, information on the execution of the deceased, and the like, and can be acquired from a bank system.
And step S120, carrying out standardization processing on the electricity utilization behavior information and the external credit investigation information.
Before performing the deep analysis on the information, it is necessary to standardize the information and perform the deep analysis using the standardized information. The information normalization process is an indexing process of statistical information. Specifically, the information standardization processing mainly comprises two aspects of data homochemotaxis processing and dimensionless processing, wherein the information homochemotaxis processing mainly solves the problem of information with different properties, the direct summation of indexes with different properties can not correctly reflect the comprehensive results of different acting forces, the change of the information properties of inverse indexes needs to be considered firstly, so that the acting forces of all the indexes on the evaluation scheme are homochemotactic, and then the summation is carried out to obtain the correct result; the information dimensionless process mainly addresses the comparability of data. There are many methods of information normalization, and in one example, a min-max normalization method may be used; in another example, a Z-score normalization method may be employed; in yet another example, a normalization method by fractional scaling may be employed. After standardization processing, the original information is converted into a non-dimensionalized index mapping evaluation value, namely, each index value is in the same quantity level, and comprehensive evaluation analysis can be carried out.
In one example, as shown in fig. 2, the step of standardizing the power consumption behavior information and the external credit information includes the steps of:
step S210, respectively identifying corresponding maximum attribute values and minimum attribute values in the electricity taking behavior information and the external credit information;
and step S220, respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner correspondingly based on each maximum attribute value and each minimum attribute value.
It should be noted that, the maximum attribute value and the minimum attribute value of the power consumption behavior information are identified, and based on the maximum attribute value and the minimum attribute value, the power consumption behavior information is normalized and mapped to be a preset mapping interval, in one example, the preset mapping interval is [0,1]. The specific mapping formula is as follows: mapped data = (mapped data-minimum attribute value)/(maximum attribute value-minimum attribute value).
The maximum attribute value and the minimum attribute value of the external credit information are identified, and based on the maximum attribute value and the minimum attribute value, the external credit information is mapped in a standardized manner as a preset mapping interval, in one example, the preset mapping interval is [0,1]. The specific mapping formula is as follows: mapped data = (mapped data-minimum attribute value)/(maximum attribute value-minimum attribute value).
And step S130, carrying out deep analysis on the standardized electricity consumption behavior information and the external credit investigation information, and establishing a characteristic project of the payment characteristics of the power consumer.
It should be noted that the deep analysis is an extraction process of the characteristics required in the electricity consumption behavior information and the external credit investigation information, and in this step, a payment characteristic layer of the power consumer is extracted, where the payment characteristics are used to record the payment behavior of the power consumer, for example, the power consumer immediately pays when receiving a payment list, the power consumer pays after a default fee occurs, and the power consumer is waived for not paying.
In one example, the payment characteristics of the power consumer are extracted based on a characteristic project, the characteristic project is a process of converting information attributes into information characteristics, the attributes represent all dimensions of information, so that better characteristics are screened, and better training information is obtained, wherein the characteristic project comprises characteristic extraction, characteristic construction and characteristic selection.
Further, in the step of performing deep analysis on the standardized power consumption behavior information and the standardized external credit investigation information to establish the feature engineering of the payment feature of the power consumer, the method for establishing the feature engineering comprises one or any combination of the following methods: a timestamp processing method, a category attribute decomposition method, a binning/partitioning method, a cross feature method, a feature selection method, a feature scaling method, a timestamp processing method, and a feature extraction method.
Step S140, a user fee urging scoring model is established based on the characteristic project of the payment characteristics of the power users.
The user charging scoring model is used for scoring the power consumption behaviors of the power users, such as the payment behaviors, based on the big data. Specifically, the user charge prompting scoring model comprises an electric charge default coefficient model, an arrearage frequency model, an electric charge defaulting coefficient model and a charge prompting sensitivity coefficient model.
In one example, the electricity rate default coefficient model is obtained based on the following formula:
wherein D represents an electricity charge default coefficient model; r represents that the user default fund should be received; n represents the total number of power consumers; l represents the interval between the month in which the default fund should be paid and the current month in the last time;
obtaining an arrearage frequency model based on the following formula:
where a represents an arrearage frequency model.
Further, an electric charge default coefficient model is obtained based on the following formula:
wherein Q represents an electric charge delinquent coefficient model; n represents the total number of power consumers; p represents the payment date; d represents the electricity charge issuing date; n represents the number of times of the total owing fee;
acquiring a sensitivity coefficient model of hastening harvest based on the following formula:
wherein C represents a catalyst trapping sensitivity coefficient model; d is a radical of 1 Represents the current month; d 2 Indicating the household date.
And step S150, scoring the power users by adopting a user fee urging scoring model, and calling a corresponding fee urging strategy according to a scoring result.
It should be noted that, the power consumer is scored according to the user fee urging scoring model, and after the scoring result comes out, a corresponding fee urging strategy is called according to the scoring result. Setting a corresponding charging urging strategy aiming at the unknown grading level in advance, for example, directly sending a payment bill to a power user with high grading; the power users with moderate scores send charge urging task lists to the mobile devices of the related working personnel so that the related working personnel urge to pay according to the charge urging task lists; and the power users with low scores stop transmitting electric energy to the power users through the power management system, wherein the high scores, the medium scores and the low scores can be determined according to local management requirements.
In each embodiment of the power consumer management method, power consumption behavior information and external credit information of a power consumer are acquired; carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information; carrying out deep analysis on the power utilization behavior information and the external credit investigation information after the standardization processing, and extracting the payment characteristics of the power consumer; establishing a user fee urging scoring model based on the payment characteristics of the power users; the method comprises the steps of adopting a user fee-urging scoring model to score power users, calling corresponding fee-urging strategies according to scoring results, achieving the purpose that the user fee-urging scoring model of the power users is established based on power utilization behavior information and external credit information, then utilizing the user fee-urging scoring model to score payment behaviors of the power users, and adopting the corresponding fee-urging strategies for the power users according to the scoring results, thereby achieving the purpose of rapidly and effectively managing the power users based on a big data technology and comprehensively managing the users in a store.
It should be understood that although the various steps in the flowcharts of fig. 1 and 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1 and 2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 3, there is provided a power consumer management device, including:
the information acquisition module 31 is used for acquiring the electricity utilization behavior information and the external credit information of the power consumer; the electricity consumption behavior information comprises business expansion information, appeal information, arrearage information and default electricity consumption information; the external credit investigation information comprises legal litigation information, court announcement information and information of the person who loses credit to be executed;
the standardization processing module 33 is used for standardizing the power utilization behavior information and the external credit information;
the characteristic engineering extraction module 35 is used for performing deep analysis on the power consumption behavior information and the external credit investigation information after the standardization processing, and establishing a characteristic engineering of the payment characteristics of the power consumer;
the model establishing module 37 is used for establishing a user fee urging scoring model based on the characteristic engineering of the payment characteristics of the power users;
and the strategy calling module 39 is used for scoring the power consumer by adopting a consumer fee-prompting scoring model and calling a corresponding fee-prompting strategy according to a scoring result.
In one embodiment, the normalization processing module includes:
the attribute value identification unit is used for respectively identifying a corresponding maximum attribute value and a corresponding minimum attribute value in the power utilization behavior information and the external credit information;
and the mapping unit is used for respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner correspondingly based on each maximum attribute value and each minimum attribute value.
For specific limitations of the power consumer management device, reference may be made to the above limitations of the power consumer management method, which are not described herein again. The modules in the power consumer management device may be wholly or partially implemented by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing data such as electric behavior information, external credit investigation information and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a power consumer management method.
It will be appreciated by those skilled in the art that the configuration shown in fig. 4 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory having a computer program stored therein and a processor that when executing the computer program performs the steps of:
acquiring power utilization behavior information and external credit information of a power consumer; the electricity consumption behavior information comprises business expansion information, appeal information, arrearage information and default electricity consumption information; the external credit investigation information comprises legal litigation information, court announcement information and information of the person who loses credit to be executed;
carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information;
carrying out deep analysis on the power utilization behavior information and the external credit investigation information after the standardization processing, and establishing a characteristic project of the payment characteristics of the power consumer;
establishing a user fee urging scoring model based on a characteristic project of payment characteristics of a power user;
and grading the power users by adopting a user fee-urging grading model, and calling a corresponding fee-urging strategy according to a grading result.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
respectively identifying a corresponding maximum attribute value and a corresponding minimum attribute value in the electricity taking behavior information and the external credit information;
and correspondingly and respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner based on each maximum attribute value and each minimum attribute value.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring power utilization behavior information and external credit investigation information of a power consumer; the electricity consumption behavior information comprises business expansion information, appeal information, arrearage information and default electricity consumption information; the external credit investigation information comprises legal litigation information, court announcement information and information of the person who loses credit to be executed;
carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information;
carrying out deep analysis on the standardized power utilization behavior information and the external credit investigation information, and establishing a characteristic project of the payment characteristics of the power consumer;
establishing a user fee urging scoring model based on the characteristic engineering of the payment characteristics of the power users;
and grading the power users by adopting a user fee-prompting grading model, and calling a corresponding fee-prompting strategy according to a grading result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
respectively identifying a corresponding maximum attribute value and a corresponding minimum attribute value in the electricity utilization behavior information and the external credit information;
and correspondingly and respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner based on each maximum attribute value and each minimum attribute value.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct Rambus Dynamic RAM (DRDRAM), and Rambus Dynamic RAM (RDRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the claims. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent application shall be subject to the appended claims.
Claims (10)
1. A power consumer management method, comprising the steps of:
acquiring power utilization behavior information and external credit investigation information of a power consumer; the electricity consumption behavior information comprises business expansion information, appeal information, arrearage information and default electricity consumption information; the external credit investigation information comprises legal litigation information, court announcement information and information of the person who loses credit to be executed;
carrying out standardized processing on the electricity utilization behavior information and the external credit investigation information;
carrying out deep analysis on the standardized power utilization behavior information and the external credit investigation information, and establishing a characteristic project of the payment characteristics of the power consumer;
establishing a user fee urging scoring model based on the characteristic project of the payment characteristics of the power users;
grading the power users by adopting the user fee-urging grading model, and calling corresponding fee-urging strategies according to the grading result;
the user fee prompting scoring model comprises an electric charge default coefficient model;
obtaining the electric charge default coefficient model based on the following formula:
wherein D represents the electricity charge default coefficient model; r i Indicating that the default fund of the ith user should be received; n represents the total number of power consumers; l represents the interval between the month that most recently produced the liquidity and the current month.
2. The power consumer management method according to claim 1, wherein the step of standardizing the power consumption behavior information and the external credit information includes the steps of:
respectively identifying a maximum attribute value and a minimum attribute value corresponding to the electricity utilization behavior information and the external credit information;
and correspondingly and respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner based on each maximum attribute value and each minimum attribute value.
3. The power consumer management method according to claim 1, wherein the consumer charging scoring model further comprises an arrearage frequency model, an electric charge defaulting coefficient model and a charging sensitivity coefficient model.
4. The power consumer management method according to claim 3,
obtaining the arrearage frequency model based on the following formula:
wherein A represents the arrearage frequency model.
5. The power consumer management method according to claim 3, wherein the electric charge delinquent coefficient model is obtained based on the following formula:
wherein Q represents the electric charge delinquent coefficient model; n represents the total number of power consumers; p i Showing the payment date of the ith user; d i Indicating the electricity fee issue date of the ith user; n is a radical of i Representing the number of times of the common arrears of the ith user;
acquiring the sensitivity coefficient model of hastening receipts based on the following formula:
wherein, C represents a catalyst trapping sensitivity coefficient model; d 1 Represents the current month; d 2 Indicating the household date.
6. The power consumer management method according to any one of claims 1 to 5, wherein in the feature engineering step of performing deep analysis on the standardized power consumption behavior information and the external credit information to establish the payment features of the power consumer, the method for establishing the feature engineering includes one or any combination of the following methods: a timestamp processing method, a category attribute decomposition method, a binning/partitioning method, a cross feature method, a feature selection method, a feature scaling method, and a feature extraction method.
7. An electrical consumer management device, comprising:
the information acquisition module is used for acquiring the power utilization behavior information and the external credit information of the power consumer; the power utilization behavior information comprises business expansion information, appeal information, arrearage information and default power utilization information; the external credit investigation information comprises legal litigation information, court announcement information and information of the person who loses credit to be executed;
the standardized processing module is used for carrying out standardized processing on the power utilization behavior information and the external credit investigation information;
the characteristic engineering extraction module is used for carrying out deep analysis on the standardized power utilization behavior information and the external credit investigation information and establishing a characteristic engineering of the payment characteristics of the power consumer;
the model establishing module is used for establishing a user fee urging scoring model based on the characteristic engineering of the payment characteristics of the power users;
the strategy calling module is used for grading the power users by adopting the user fee-prompting grading model and calling corresponding fee-prompting strategies according to the grading result; the user fee prompting scoring model comprises an electric charge default coefficient model;
obtaining the electric charge default coefficient model based on the following formula:
wherein D represents the electricity charge default coefficient model; r is i Indicating that the default fund of the ith user should be received; n represents the total number of power consumers; l represents the interval between the month that most recently produced the liquidity and the current month.
8. The power consumer management device according to claim 7, wherein the normalization processing module comprises:
an attribute value identification unit, configured to respectively identify a maximum attribute value and a minimum attribute value corresponding to the power consumption behavior information and the external credit investigation information;
and the mapping unit is used for correspondingly and respectively mapping the power utilization behavior information and the external credit investigation information into a preset mapping interval in a standardized manner based on each maximum attribute value and each minimum attribute value.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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