CN110910009B - Power consumer management method and device, computer equipment and storage medium - Google Patents

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

Power user management method, device, computer equipment and storage medium

technical field

The present application relates to the technical field of power user management, in particular to a power user management method, device, computer equipment and storage medium.

Background technique

As the growth rate of the social economy gradually slows down, the downward pressure on the economy gradually increases, and the pressure on electricity charge recovery is increasing day by day. Faced with different types of electricity users in the society, power suppliers can only take prevention and control measures for all of a certain type of electricity users for risk management, and cannot quantify or group control. In addition, in order to complete the task of electricity fee recovery, the workload of monthly reminders accounts for about half of the total workload, which has a serious impact on the promotion of other businesses and low work efficiency.

At present, the payment reminder method adopted has always remained in the original inherent mode, such as unified payment reminder when due, unified power outage when due, etc. Although the above method is standardized, it is not the optimal payment method. For example, for some power users, regardless of No matter how the staff urges them to pay, they only pay at a certain fixed time; some power users have a good payment record and suddenly owe their bills; , there are different reasons behind the behavior of each power user. Therefore, during the implementation process, the inventor found at least the following problems in the traditional technology: the traditional technology cannot effectively and comprehensively manage power users.

Contents of the invention

Based on this, it is necessary to provide a power user management method, device, computer equipment and storage medium capable of reasonably managing power users in order to address the above technical problems.

A power user management method, comprising the following steps:

Obtain electricity consumption behavior information and external credit investigation information of power users; electricity consumption behavior information includes business expansion application information, appeal information, arrears information and default electricity consumption information; external credit investigation information includes legal proceedings information, court announcement information and information on the execution of dishonest persons;

Standardize the electricity consumption behavior information and external credit information;

Carry out in-depth analysis of the standardized power consumption behavior information and external credit information, and establish the feature engineering of the payment characteristics of power users;

Based on the payment characteristics of power users, a user reminder scoring model is established;

Use the user reminder scoring model to score power users, and call the corresponding reminder strategy based on the scoring results.

In one of the embodiments, the step of standardizing the electricity usage behavior information and external credit information includes the steps of:

Respectively identify the corresponding maximum attribute value and minimum attribute value in the electricity consumption behavior information and external credit information;

Based on each maximum attribute value and each minimum attribute value, the electricity consumption behavior information and external credit information are respectively standardized and mapped into the preset mapping interval.

In one of the embodiments, the user reminder scoring model includes an electricity fee default coefficient model, an arrears frequency model, an electricity fee arrears coefficient model, and a collection sensitivity coefficient model.

In one of the embodiments, the electricity default coefficient model is obtained based on the following formula:

Among them, D represents the electricity fee default coefficient model; R represents the liquidated damages receivable from users; n represents the total number of power users; L represents the interval between the month when the most recent liquidated damages receivable occurred and the current month;

Obtain the arrears frequency model based on the following formula:

Among them, A represents the arrears frequency model.

In one of the embodiments, the electricity bill arrears coefficient model is obtained based on the following formula:

Among them, Q represents the coefficient model of electricity bill arrears; n represents the total number of power users; P represents the date of payment; D represents the date of electricity bill issuance; N represents the total number of arrears;

Obtain the collection sensitivity coefficient model based on the following formula:

Among them, C represents the collection sensitivity coefficient model; d ₁ represents the current month; d ₂ represents the date of account opening.

In one of the embodiments, in-depth analysis is carried out on the standardized processing of electricity consumption behavior information and external credit information, and in the feature engineering step of establishing the payment characteristics of power users, the method of establishing feature engineering includes one of the following methods or Any combination of: timestamp processing methods, decomposing category attribute methods, binning/partitioning methods, cross-feature methods, feature selection methods, feature scaling methods, and feature extraction methods.

A power user management device, comprising:

The information acquisition module is used to obtain electricity consumption behavior information and external credit information of power users; electricity consumption behavior information includes business expansion application information, appeal information, arrears information, and breach of contract electricity consumption information; external credit information includes legal proceedings Information, court announcement information and information on the enforcement of dishonest persons;

Standardized processing module, used for standardized processing of electricity consumption behavior information and external credit information;

The feature engineering extraction module is used for in-depth analysis of the standardized processing of electricity consumption behavior information and external credit information, and the establishment of feature engineering of the payment characteristics of power users;

The model building module is used for feature engineering based on the payment characteristics of electric power users, and establishes a user reminder scoring model;

The strategy invoking module is used to use the user fee reminder scoring model to score the power users, and call the corresponding fee reminder strategy according to the score result.

In one of the embodiments, the standardized processing module includes:

The attribute value recognition unit is used to respectively recognize the corresponding maximum attribute value and minimum attribute value in the electricity consumption behavior information and the external credit information;

The mapping unit is configured to standardize and map electricity consumption behavior information and external credit information into preset mapping intervals based on each maximum attribute value and each minimum attribute value.

A computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are realized.

One of the above technical solutions has the following advantages and beneficial effects:

The power user management method provided by each embodiment of the present application goes through the following steps: acquiring power user’s power usage behavior information and external credit information; standardizing the power usage behavior information and external credit information; Conduct in-depth analysis of behavior information and external credit information to extract the payment characteristics of power users; establish a user reminder scoring model based on the payment characteristics of power users; use the user reminder scoring model to score power users, and call the corresponding Based on the electricity consumption behavior information and external credit information, the user reminder scoring model of power users can be established, and then the user reminder scoring model can be used to score the payment behavior of power users, and according to the scoring results, corresponding measures can be taken for power users. To realize the rapid and effective management of power users based on big data technology, and to coordinate the management of users in the store.

Description of drawings

Fig. 1 is a schematic flow chart of a power user management method in an embodiment;

Fig. 2 is a schematic flow chart of standardization processing steps in an embodiment;

Fig. 3 is a structural block diagram of a power user management device in an embodiment;

Figure 4 is an internal block diagram of a computer device in one embodiment.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

In order to solve the problem that traditional technologies cannot effectively and comprehensively manage power users, in one embodiment, as shown in Figure 1, a method for managing power users is provided, including the following steps:

Step S110, obtain electricity consumption behavior information and external credit investigation information of electric power users; electricity consumption behavior information includes business expansion application information, appeal information, arrears information and breach of contract electricity consumption information; external credit investigation information includes legal proceedings information, court Announcement information and information on the execution of dishonest persons.

It should be noted that this application is implemented based on big data technology. In one example, spark technology or hadoop technology can be used to implement the method steps of this application. Through the big data platform, it can be said that this application provides basic data storage capabilities and powerful data processing capabilities.

Electricity consumption behavior information refers to information such as business expansion application information, appeal information, arrears information, and power consumption information in breach of contract, which can be obtained from the grid marketing system; external credit information refers to legal litigation information, court announcement information, and dishonesty information. Information such as executed information can be obtained from the banking system.

Step S120, standardize the electricity usage behavior information and external credit information.

It should be noted that before in-depth analysis of information, it is necessary to standardize the information first, and then use the standardized information for in-depth analysis. Information standardization refers to the indexation of statistical information. Specifically, information standardization processing mainly includes two aspects: data homogeneity processing and dimensionless processing. Among them, information homogeneity processing mainly solves the problem of information of different natures, and direct summation of different nature indicators cannot correctly reflect different forces. To synthesize the results, we must first consider changing the information properties of the inverse indicators, so that all indicators have the same force on the evaluation plan, and then sum up to get the correct result; the dimensionless processing of information mainly solves the comparability of data. There are many ways to normalize information. In one example, the minimum-maximum normalization method can be used; in another example, the Z-score normalization method can be used; in another example, the decimal scaling normalization method can be used . After standardized processing, the original information is converted into dimensionless index evaluation values, that is, each index value is at the same quantitative level, and comprehensive evaluation and analysis can be performed.

In one example, as shown in Figure 2, the steps of standardizing the electricity usage behavior information and external credit information include the steps:

Step S210, respectively identifying the corresponding maximum attribute value and minimum attribute value in the electricity usage behavior information and external credit information;

Step S220, based on each maximum attribute value and each minimum attribute value, respectively standardize and map electricity consumption behavior information and external credit information into a preset mapping interval.

It should be noted that the maximum attribute value and the minimum attribute value of the electricity consumption behavior information are recognized, and based on the maximum attribute value and the minimum attribute value, the electricity consumption behavior information is standardized and mapped as a preset mapping interval. In one example, the preset The mapping interval is [0, 1]. The specific mapping formula is: mapped data=(mapped data-minimum attribute value)/(maximum attribute value-minimum attribute value).

Recognize the maximum attribute value and the minimum attribute value of the external credit information, and based on the maximum attribute value and the minimum attribute value, standardize the external credit information mapping as a preset mapping interval. In one example, the preset mapping interval is [0 ,1]. The specific mapping formula is: mapped data=(mapped data-minimum attribute value)/(maximum attribute value-minimum attribute value).

Step S130, conduct in-depth analysis on the standardized processing of electricity consumption behavior information and external credit information, and establish a feature engineering of payment characteristics of power users.

It should be noted that in-depth analysis is the process of extracting required features from electricity consumption behavior information and external credit information. In this step, the payment feature layer of power users is extracted, and the payment features are used to record power user For example, power users pay immediately when they receive the bill of payment, power users pay only after there is a penalty for breach of contract, and power users have been in arrears and have not paid.

In one example, feature engineering is used to extract the payment features of power users. Feature engineering is the process of converting information attributes into information features. Attributes represent all dimensions of information, so as to filter out better features and obtain better training information. , feature engineering includes feature extraction, feature construction, and feature selection.

Further, in the feature engineering step of establishing the payment characteristics of power users by in-depth analysis of the standardized electricity consumption behavior information and external credit information, the feature engineering method includes one or any combination of the following methods: Timestamp processing methods, decomposing category attribute methods, binning/partitioning methods, cross-feature methods, feature selection methods, feature scaling methods, timestamp processing methods, and feature extraction methods.

Step S140, based on the feature engineering of the electricity user's payment characteristics, a user reminder scoring model is established.

It should be noted that the user reminder scoring model is used to score the power consumption behavior of power users, such as payment behavior, based on big data. Specifically, the user reminder scoring model includes an electricity fee default coefficient model, an arrears frequency model, an electricity fee arrears coefficient model, and a collection sensitivity coefficient model.

In one example, the electricity default coefficient model is obtained based on the following formula:

Among them, D represents the electricity fee default coefficient model; R represents the liquidated damages receivable from users; n represents the total number of power users; L represents the interval between the month when the most recent liquidated damages receivable occurred and the current month;

Obtain the arrears frequency model based on the following formula:

Among them, A represents the arrears frequency model.

Further, the electricity fee arrears coefficient model is obtained based on the following formula:

Among them, Q represents the coefficient model of electricity bill arrears; n represents the total number of power users; P represents the date of payment; D represents the date of electricity bill issuance; N represents the total number of arrears;

Obtain the collection sensitivity coefficient model based on the following formula:

Among them, C represents the collection sensitivity coefficient model; d ₁ represents the current month; d ₂ represents the date of account opening.

Step S150, using the user fee reminder scoring model to rate the power user, and call the corresponding fee reminder strategy according to the score result.

It should be noted that the power users are scored according to the user reminder scoring model, and after the scoring results come out, the corresponding reminder strategies are invoked according to the scoring results. Set the corresponding payment reminder strategy in advance for the rating level that you don’t understand. For example, electricity users with high scores will send payment bills directly to them; electricity users with medium scores will send payment reminder tasks to relevant staff’s mobile devices. To enable relevant staff to urge payment according to the urging task list; power users with low scores stop sending power to them through the power management system, among which, high, medium, and low scores can be determined according to local management needs.

In each embodiment of the power user management method of the present application, the power consumption behavior information and external credit information of power users are obtained; the power consumption behavior information and external credit information are standardized; the standardized power consumption behavior information and Conduct in-depth analysis of external credit information to extract the payment characteristics of power users; establish a user reminder scoring model based on the payment characteristics of power users; use the user reminder scoring model to score power users, and call the corresponding payment reminder based on the scoring results Based on the electricity consumption behavior information and external credit information, the user reminder scoring model for power users can be established, and then the user reminder scoring model can be used to score the payment behavior of power users, and according to the scoring results, corresponding payment reminders can be adopted for power users strategy, so as to realize the rapid and effective management of power users based on big data technology, and coordinate the management of users in the store.

It should be understood that although the various steps in the flow charts of FIGS. 1 and 2 are displayed sequentially as indicated by the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in Figures 1 and 2 may include a plurality of sub-steps or stages, these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times, these sub-steps or stages The order of execution is not necessarily performed sequentially, but may be performed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

In one embodiment, as shown in Figure 3, a power user management device is provided, including:

The information acquisition module 31 is used to acquire electricity consumption behavior information and external credit investigation information of power users; the electricity consumption behavior information includes business expansion application information, appeal information, arrears information, and default electricity consumption information; external credit investigation information includes legal Litigation information, court announcement information, and information on the enforcement of dishonest persons;

Standardization processing module 33, used for standardization processing of electricity consumption behavior information and external credit information;

The feature engineering extraction module 35 is used to conduct in-depth analysis of the standardized processing of electricity consumption behavior information and external credit information, and establish feature engineering of the payment characteristics of power users;

The model building module 37 is used for feature engineering based on the payment characteristics of electric power users to establish a user reminder scoring model;

The strategy invoking module 39 is used to use the user fee reminder scoring model to score the power users, and call the corresponding fee reminder strategy according to the score result.

In one embodiment, the normalization processing module includes:

The attribute value recognition unit is used to respectively recognize the corresponding maximum attribute value and minimum attribute value in the electricity consumption behavior information and the external credit information;

The mapping unit is configured to standardize and map electricity consumption behavior information and external credit information into preset mapping intervals based on each maximum attribute value and each minimum attribute value.

For the specific limitations of the power user management device, please refer to the above-mentioned definition of the power user management method, which will not be repeated here. Each module in the above electric power user management device can be fully or partially realized by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, and can also be stored in the memory of the computer device in the form of software, so that the processor can invoke and execute the corresponding operations of the above-mentioned modules.

In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure may be as shown in FIG. 4 . The computer device includes a processor, memory, network interface and database connected by a system bus. Wherein, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs and databases. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used to store data such as electrical behavior information and external credit information. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a power user management method is realized.

Those skilled in the art can understand that the structure shown in Figure 4 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation to the computer equipment on which the solution of the application is applied. The specific computer equipment can be More or fewer components than shown in the figures may be included, or some components may be combined, or have a different arrangement of components.

In one embodiment, a computer device is provided, including a memory and a processor, a computer program is stored in the memory, and the processor implements the following steps when executing the computer program:

Obtain electricity consumption behavior information and external credit investigation information of power users; electricity consumption behavior information includes business expansion application information, appeal information, arrears information and default electricity consumption information; external credit investigation information includes legal proceedings information, court announcement information and information on the execution of dishonest persons;

Standardize the electricity consumption behavior information and external credit information;

Carry out in-depth analysis of the standardized processing of electricity consumption behavior information and external credit information, and establish the feature engineering of the payment characteristics of power users;

Based on the feature engineering of the payment characteristics of power users, a user reminder scoring model is established;

Use the user reminder scoring model to score power users, and call the corresponding reminder strategy based on the scoring results.

In one embodiment, the following steps are also implemented when the processor executes the computer program:

Respectively identify the corresponding maximum attribute value and minimum attribute value in the electricity consumption behavior information and external credit information;

Based on each maximum attribute value and each minimum attribute value, the electricity consumption behavior information and external credit information are respectively standardized and mapped into the preset mapping interval.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

Obtain electricity consumption behavior information and external credit investigation information of power users; electricity consumption behavior information includes business expansion application information, appeal information, arrears information and default electricity consumption information; external credit investigation information includes legal proceedings information, court announcement information and information on the execution of dishonest persons;

Standardize the electricity consumption behavior information and external credit information;

Carry out in-depth analysis of the standardized processing of electricity consumption behavior information and external credit information, and establish the feature engineering of the payment characteristics of power users;

Based on the feature engineering of the payment characteristics of power users, a user reminder scoring model is established;

Use the user reminder scoring model to score power users, and call the corresponding reminder strategy based on the scoring results.

In one embodiment, when the computer program is executed by the processor, the following steps are also implemented:

Respectively identify the corresponding maximum attribute value and minimum attribute value in the electricity consumption behavior information and external credit information;

Based on each maximum attribute value and each minimum attribute value, the electricity consumption behavior information and external credit information are respectively standardized and mapped into the preset mapping interval.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented through computer programs to instruct related hardware, and the computer programs can be stored in a non-volatile computer-readable memory In the medium, when the computer program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, any references to memory, storage, database or other media used in the various embodiments provided in the present application may include non-volatile and/or volatile memory. Nonvolatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be It is considered to be within the range described in this specification.

The above-mentioned embodiments only express several implementation modes of the present application, and the description thereof is relatively specific and detailed, but should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the scope of protection of the patent application should be based on 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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