Express network operation evaluation method, device and equipment and storage medium

Abstract

The invention discloses an express delivery network operation evaluation method, and the method comprises the steps: obtaining express delivery network operation data, which is used for obtaining an evaluation factor set affecting the operation of an express delivery network and the historical operation data of the express delivery network; determining a feature data set according to the evaluation factor set influencing the operation of the express network; building a website operation evaluation model, training the website operation evaluation model by using the feature data set and the website historical operation data, and determining the trained website operation evaluation model; inputting the historical operation data of the express delivery network into the network operation evaluation model to output a network operation evaluation result; and adjusting related parameters of the network operation evaluation model based on the evaluation result. According to the method, the evaluation factors influencing operation can be determined, the operation state of the express delivery network can be effectively and accurately evaluated through the operation data, and meanwhile, the express delivery network with the poor operation state can be effectively supervised and optimized.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to an express delivery network operation evaluation method, device, equipment and storage medium. Background Art

[0002] With the rapid development of e-commerce, the scale of the logistics industry continues to expand, and the number of express delivery outlets is also increasing. However, different express delivery outlets face various problems in the operation process, such as personnel management, equipment maintenance, service quality, etc. These problems directly affect the operational health level and operational efficiency of express delivery outlets. Therefore, how to effectively and accurately evaluate the operational health level of express delivery outlets from a comprehensive perspective, effectively supervise and optimize express delivery outlets with poor operating conditions, and perform intelligent matching has become an urgent problem to be solved in the express delivery industry.

[0003] In order to effectively and accurately evaluate the operating status of express delivery outlets and to effectively supervise and optimize express delivery outlets with poor operating conditions, it is necessary to invent an express delivery outlet operation evaluation method, device, equipment and storage medium. Summary of the invention

[0004] The main purpose of the present invention is to solve the technical problem that the existing technology cannot effectively and accurately evaluate the operating status of express delivery outlets, and at the same time can effectively supervise and optimize express delivery outlets with poor operating conditions.

[0005] A first aspect of the present invention provides a method for evaluating express delivery outlet operations, the method comprising: Acquire express outlet operation data, which is used to obtain a set of factors affecting express outlet operation evaluation and express outlet historical operation data; Determining a feature data set based on a set of evaluation factors affecting the express delivery outlet operations; Build a branch operation evaluation model, use the feature data set and branch historical operation data to train the branch operation evaluation model, and determine the trained branch operation evaluation model; Inputting the historical operation data of the express delivery outlets into the outlet operation evaluation model to output the outlet operation evaluation results; Based on the evaluation results, relevant parameters of the network point operation evaluation model are adjusted.

[0006] Optionally, in a first implementation of the first aspect of the present invention, the obtaining of express outlet operation data is used to obtain a set of evaluation factors affecting express outlet operation and historical operation data of the express outlets, including: Analyze the business process of the express outlet operation, determine the factors affecting the express outlet operation evaluation, and obtain the set of factors affecting the express outlet operation evaluation formed by the factors; By connecting to the database system of the express delivery outlet, the historical operation data of the express delivery outlet is obtained; Using a data cleaning algorithm, the historical operating data of the express delivery outlets is standardized and converted into a unified format.

[0007] Optionally, in a second implementation of the first aspect of the present invention, determining the feature data set according to the set of factors affecting the express outlet operation evaluation includes: Analyze the factors in the set of factors affecting the express delivery outlet operation evaluation to determine the degree of their influence on the express delivery outlet operation evaluation; Selecting factors that have a significant impact on the express outlet operation evaluation from the factor set as feature variables, and quantifying the feature variables to obtain quantified feature data; The quantified feature data are combined into a feature data set.

[0008] Optionally, in a third implementation of the first aspect of the present invention, the building of the network operation evaluation model, training the network operation evaluation model using the feature data set and the network historical operation data, and determining the trained network operation evaluation model include: Selecting a suitable learning algorithm according to the feature data set and the historical operation data; Using the feature data set and the historical operation data as input to train the model; Evaluate the trained model and adjust the model parameters until the predetermined evaluation criteria are met; Determine the trained outlet operation evaluation model.

[0009] Optionally, in a fourth implementation of the first aspect of the present invention, inputting the historical operation data of the express outlets into the outlet operation evaluation model to output an outlet operation evaluation result includes: Presetting the health level and health level threshold of the express delivery outlet operation; Inputting the historical operation data of the express outlets into the outlet operation evaluation model, and outputting the operation evaluation results of the express outlets; The operation evaluation result is compared with the threshold value of the health level, and the health level of the express outlet operation is determined based on the comparison result, and the health level includes at least healthy, sub-healthy, unhealthy and other categories.

[0010] Optionally, in a fifth implementation of the first aspect of the present invention, adjusting relevant parameters of the network point operation evaluation model based on the evaluation result includes: Preset evaluation criteria for the operation of the express delivery outlets; Analyze the evaluation results of the express delivery outlet operations and determine the deviation of the evaluation model during the evaluation process; Adjust relevant parameters of the network point operation evaluation model according to the deviation; Repeat the above steps until the model evaluation results meet the preset evaluation criteria.

[0011] Optionally, in a sixth implementation of the first aspect of the present invention, adjusting relevant parameters of the network point operation evaluation model based on the evaluation result further includes: Obtain the health level assessment results of the express delivery outlet operations; Determining the health level of the express delivery outlet operation according to the health level assessment result; According to the health level of the express outlets, potential franchise areas around the express outlets are matched; According to the health level of the express delivery outlets, corresponding management strategies and resource allocation plans are planned for the franchise intention area, and the plans at least include increasing personnel and equipment investment and optimizing work flow measures.

[0012] A second aspect of the present invention provides an express delivery outlet operation evaluation device, comprising: The module for obtaining express outlet operation data is used to obtain the set of factors affecting express outlet operation evaluation and the historical operation data of express outlets; A feature data set determination module, used to determine a feature data set according to a set of factors affecting the express outlet operation evaluation; Build an outlet operation evaluation model module to train the outlet operation evaluation model using feature data sets and outlet historical operation data, and determine the trained outlet operation evaluation model; An evaluation module, used to input the historical operation data of the express outlets into the outlet operation evaluation model to output an outlet operation evaluation result; An adjustment module is used to adjust relevant parameters of the network point operation evaluation model based on the evaluation result.

[0013] A third aspect of the present invention provides a computer device, the computer device comprising a memory and at least one processor, the memory storing instructions; The at least one processor calls the instructions in the memory so that the computer device executes the express delivery outlet operation evaluation method as described above.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is loaded by a processor to execute the express delivery outlet operation evaluation method as described in any one of the above items.

[0015] The express delivery outlet operation evaluation method of the present invention can determine the factors affecting the express delivery outlet operation evaluation, and effectively and accurately evaluate the operation status of the express delivery outlet through the operation data of the outlet, so that the operation health status of the express delivery outlet can be scientifically and reasonably evaluated, and at the same time, it can effectively supervise and optimize the express delivery outlets with poor operation status. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of a method for evaluating express delivery outlet operations provided by an embodiment of the present invention; Figure 2 A flow chart of obtaining express outlet operation data in the express outlet operation evaluation method provided in an embodiment of the present invention; Figure 3 A flow chart of determining a feature data set in the express delivery outlet operation evaluation method provided in an embodiment of the present invention; Figure 4 A flow chart of building an express delivery outlet operation evaluation model in the express delivery outlet operation evaluation method provided in an embodiment of the present invention; Figure 5 A flow chart of outputting an outlet operation evaluation result in the express outlet operation evaluation method provided in an embodiment of the present invention; Figure 6 A flow chart of adjusting parameters of an express delivery outlet operation evaluation model in the express delivery outlet operation evaluation method provided in an embodiment of the present invention; Figure 7 A schematic diagram of the structure of an express delivery outlet operation evaluation device provided by an embodiment of the present invention; Figure 8 Another structural schematic diagram of the express delivery outlet operation evaluation device provided by an embodiment of the present invention; Fig. 9 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The present invention provides an express network point operation evaluation method, the method comprising: obtaining express network point operation data, which is used to obtain a set of factors affecting the express network point operation evaluation and the express network point historical operation data; determining a feature data set according to the set of factors affecting the express network point operation evaluation; building a network point operation evaluation model, using the feature data set and the network point historical operation data to train the network point operation evaluation model, and determining the trained network point operation evaluation model; inputting the express network point historical operation data into the network point operation evaluation model to output the network point operation evaluation result; and adjusting the relevant parameters of the network point operation evaluation model based on the evaluation result.

[0018] The express delivery outlet operation evaluation method of the present invention can determine the factors affecting the express delivery outlet operation evaluation, and effectively and accurately evaluate the operation status of the express delivery outlet through the operation data of the outlet, so that the operation health status of the express delivery outlet can be scientifically and reasonably evaluated, and at the same time, it can effectively supervise and optimize the express delivery outlets with poor operation status.

[0019] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0020] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the present invention provides a method for evaluating the operation of an express delivery outlet, the method comprising: 101. Obtaining express outlet operation data, which is used to obtain a set of factors affecting express outlet operation evaluation and historical operation data of express outlets; 102. Determine a feature data set according to a set of factors affecting the express delivery outlet operation evaluation; 103. Build a branch operation evaluation model, train the branch operation evaluation model using feature data sets and branch historical operation data, and determine the trained branch operation evaluation model; 104. Inputting the historical operation data of the express delivery outlets into the outlet operation evaluation model to output an outlet operation evaluation result; 105. Based on the evaluation result, adjust relevant parameters of the network point operation evaluation model.

[0021] The express delivery outlet operation evaluation method of the present invention can determine the factors affecting the express delivery outlet operation evaluation, and effectively and accurately evaluate the operation status of the express delivery outlet through the operation data of the outlet, so that the operation health status of the express delivery outlet can be scientifically and reasonably evaluated, and at the same time, it can effectively supervise and optimize the express delivery outlets with poor operation status.

[0022] See also Figure 2 In a second embodiment of the express outlet operation evaluation method in an embodiment of the present invention, based on the above embodiment, the express outlet operation data is obtained, which is used to obtain a set of factors affecting the express outlet operation evaluation and the express outlet historical operation data, including: 201. Analyze the business process of the express outlet operation, determine the factors affecting the express outlet operation evaluation, and obtain a set of factors affecting the express outlet operation evaluation formed by the factors; 202. Acquire historical operation data of the express delivery outlet by connecting to the database system of the express delivery outlet; In some embodiments, the basic information, operation data, personnel data and equipment data are obtained by connecting to the database system of the express delivery outlet or using a data collection tool.

[0023] In some embodiments, basic information of the express delivery outlets is collected, including but not limited to the outlet name, address, person in charge, etc.; In some embodiments, the operational data of the express delivery outlets are collected, and the operational data includes but is not limited to the number of received parcels, the number of delivered parcels, the number of complaints, the delay rate, etc.; In some embodiments, personnel data of the express delivery outlets is collected, and the personnel data includes but is not limited to the number of employees, employee working hours, employee training status, etc.; In some embodiments, equipment data of the express delivery outlets is collected, and the equipment data includes but is not limited to the number of vehicles, equipment maintenance records, etc.; 203. Use a data cleaning algorithm to standardize the historical operation data of the express delivery outlets and convert them into a unified format.

[0024] The embodiments of the present invention can scientifically and reasonably analyze the evaluation factors that affect the operation of express delivery outlets, and ensure the comprehensiveness and objectivity of the evaluation results by comprehensively considering various factors that affect the operation evaluation of express delivery outlets; by accurately collecting and processing historical operation data, the accuracy of the evaluation results is improved, which helps to more accurately judge the operation status of the outlets; the data obtained in real time or regularly can timely reflect the latest operation status of the outlets. The automatic collection and processing of data reduces the need for manual operation, reduces the error rate, and improves work efficiency.

[0025] See also Figure 3 In a third embodiment of the express delivery outlet operation evaluation method in an embodiment of the present invention, the step of determining a feature data set based on a set of factors affecting the express delivery outlet operation evaluation comprises: 301. Analyze the factors in the set of factors affecting the express delivery outlet operation evaluation to determine the degree of their influence on the express delivery outlet operation evaluation; 302. Selecting factors that have a significant impact on the express outlet operation evaluation from the factor set as feature variables, and quantifying the feature variables to obtain quantified feature data; 303. Combining the quantified feature data into a feature data set.

[0026] The feature data set determined by the embodiment of the present invention can be used as the input of the evaluation model to provide scientific decision-making support for management and help formulate effective improvement measures; through feature selection and engineering, redundant data can be reduced, the data processing process can be simplified, and the data processing efficiency can be improved; the carefully selected feature data set can enhance the learning effect of the model and improve the prediction accuracy and generalization ability of the model.

[0027] See also Figure 4 In the fourth embodiment of the express delivery outlet operation evaluation method in the embodiments of the present invention, the outlet operation evaluation model is constructed, the outlet operation evaluation model is trained using the feature data set and the outlet historical operation data, and the trained outlet operation evaluation model is determined, including: 401. Selecting a suitable learning algorithm according to the feature data set and the historical operation data; 402. Use the feature data set and the historical operation data as input to train the model; 403. Evaluate the trained model and adjust the model parameters until a predetermined evaluation standard is met; 404. Determine the trained outlet operation evaluation model.

[0028] The embodiments of the present invention utilize feature data sets and historical operation data to train models, thereby being able to more accurately evaluate the operating conditions of outlets and provide reliable results; by continuously adjusting model parameters and retraining, the performance of the model can be continuously improved so that it can better adapt to the ever-changing operating environment.

[0029] See also Figure 5 In a fifth embodiment of the express delivery outlet operation evaluation method in the embodiment of the present invention, the step of inputting the express delivery outlet historical operation data into the outlet operation evaluation model to output an outlet operation evaluation result includes: 501. Preset the health level and health level threshold of the express delivery outlet operation; 502. Input the historical operation data of the express outlet into the outlet operation evaluation model, and output the operation evaluation result of the express outlet; 503. Compare the operation evaluation result with the threshold of the health level, and determine the health level of the express outlet operation based on the comparison result, where the health level includes at least healthy, sub-healthy, unhealthy and other categories.

[0030] The evaluation results output by the embodiment of the present invention provide the management with a detailed basis for operation analysis, making the operation decision-making process more scientific and reliable, and facilitating the formulation of more targeted operation management measures.

[0031] See also Figure 6 In the sixth embodiment of the express delivery outlet operation evaluation method in the embodiment of the present invention, adjusting the relevant parameters of the outlet operation evaluation model based on the evaluation result includes: 601. Preset the evaluation criteria for the operation of the express delivery outlets; 602. Analyze the evaluation results of the express delivery outlet operations to determine the deviation of the evaluation model during the evaluation process; 603. Adjust relevant parameters of the network point operation evaluation model according to the deviation; 604. Repeat the above steps until the model evaluation result meets the preset evaluation criteria.

[0032] The embodiments of the present invention can improve the prediction accuracy of the model by adjusting the model parameters, making the evaluation results more accurate and better reflecting the actual operating conditions of the outlets; adjusting the parameters can reduce the possibility of model misjudgment, improve the credibility of the evaluation results, and reduce losses caused by evaluation errors.

[0033] Furthermore, adjusting the relevant parameters of the network point operation evaluation model based on the evaluation result also includes: Obtain the health level assessment results of the express delivery outlet operations; Determining the health level of the express delivery outlet operation according to the health level assessment result; According to the health level of the express outlets, potential franchise areas around the express outlets are matched; According to the health level of the express delivery outlets, corresponding management strategies and resource allocation plans are planned for the franchise intention area, and the plans at least include increasing personnel and equipment investment and optimizing work flow measures.

[0034] The embodiment of the present invention can find the corresponding franchise intention area according to the evaluation results. For healthy outlets, maintain the existing resource configuration and perform light optimization. For sub-healthy outlets, analyze their existing problems, such as insufficient staff or aging equipment, and increase staff recruitment plans or arrange equipment updates accordingly. For unhealthy outlets, conduct a comprehensive diagnosis and formulate detailed improvement plans, including substantial investment in personnel and equipment, as well as in-depth optimization of work processes.

[0035] The above describes the express delivery network point operation evaluation method in the embodiment of the present invention. The following describes the express delivery network point operation evaluation device in the embodiment of the present invention. Figure 7 In one embodiment of the present invention, an express delivery outlet operation evaluation device includes: The express outlet operation data acquisition module 701 is used to acquire a set of evaluation factors affecting the express outlet operation and the express outlet historical operation data; A feature data set determination module 702 is used to determine a feature data set according to a set of factors affecting the express delivery outlet operation evaluation; Building a network point operation evaluation model module 703, which is used to train the network point operation evaluation model using the feature data set and the network point historical operation data, and determine the trained network point operation evaluation model; Evaluation module 704, used for inputting the historical operation data of the express outlets into the outlet operation evaluation model to output an outlet operation evaluation result; The adjustment module 705 is used to adjust relevant parameters of the network point operation evaluation model based on the evaluation result.

[0036] The express delivery outlet operation evaluation device of the present invention can determine the factors affecting the express delivery outlet operation evaluation, and effectively and accurately evaluate the operation status of the express delivery outlet through the outlet operation data, so that the operation health status of the express delivery outlet can be scientifically and reasonably evaluated, and at the same time, it can effectively supervise and optimize the express delivery outlets with poor operation status.

[0037] See also Figure 8 Another embodiment of the express delivery outlet operation evaluation device in the embodiment of the present invention includes: The express outlet operation data acquisition module 701 is used to acquire a set of evaluation factors affecting the express outlet operation and the express outlet historical operation data; In some embodiments, the module 701 for obtaining express delivery outlet operation data includes: The first acquisition unit 7011 is used to analyze the business process of the express outlet operation, determine the factors affecting the express outlet operation evaluation, and obtain the set of factors affecting the express outlet operation evaluation formed by the factors; The second acquisition unit 7012 is used to acquire the historical operation data of the express delivery outlet by connecting to the database system of the express delivery outlet; In some embodiments, the basic information, operation data, personnel data and equipment data are obtained by connecting to the database system of the express delivery outlet or using a data collection tool.

[0038] In some embodiments, basic information of the express delivery outlets is collected, including but not limited to the outlet name, address, person in charge, etc.; In some embodiments, the operational data of the express delivery outlets are collected, and the operational data includes but is not limited to the number of received parcels, the number of delivered parcels, the number of complaints, the delay rate, etc.; In some embodiments, personnel data of the express delivery outlets is collected, and the personnel data includes but is not limited to the number of employees, employee working hours, employee training status, etc.; In some embodiments, equipment data of the express delivery outlets is collected, and the equipment data includes but is not limited to the number of vehicles, equipment maintenance records, etc.; The data cleaning unit 7013 is used to use a data cleaning algorithm to standardize the historical operation data of the express delivery outlets and convert them into a unified format.

[0039] The embodiments of the present invention can scientifically and reasonably analyze the evaluation factors that affect the operation of express delivery outlets, and ensure the comprehensiveness and objectivity of the evaluation results by comprehensively considering various factors that affect the operation evaluation of express delivery outlets; by accurately collecting and processing historical operation data, the accuracy of the evaluation results is improved, which helps to more accurately judge the operation status of the outlets; the data obtained in real time or regularly can timely reflect the latest operation status of the outlets. The automatic collection and processing of data reduces the need for manual operation, reduces the error rate, and improves work efficiency.

[0040] In some embodiments, the feature data set determination module 702 is used to determine the feature data set according to the set of factors affecting the express delivery outlet operation evaluation; In some embodiments, the determining feature data set module 702 includes: The first analysis unit 7021 is used to analyze the factors in the set of factors affecting the express delivery outlet operation evaluation to determine the degree of their influence on the express delivery outlet operation evaluation; A quantification unit 7022 is used to select factors that have a significant impact on the express outlet operation evaluation from the factor set as feature variables, and quantify the feature variables to obtain quantified feature data; The combining unit 7023 is used to combine the quantized feature data into a feature data set.

[0041] The feature data set determined in this embodiment can be used as the input of the evaluation model to provide scientific decision-making support for management and help formulate effective improvement measures; through feature selection and engineering, redundant data can be reduced, the data processing process can be simplified, and the data processing efficiency can be improved; the carefully selected feature data set can enhance the learning effect of the model and improve the prediction accuracy and generalization ability of the model.

[0042] In some embodiments, a network point operation evaluation model module 703 is constructed to train the network point operation evaluation model using the feature data set and the network point historical operation data, and determine the trained network point operation evaluation model; In some embodiments, the building of the network operation evaluation model module 703 includes: A selection unit 7031, configured to select a suitable learning algorithm according to the feature data set and the historical operation data; An input training unit 7032, configured to train the model using the feature data set and the historical operation data as input; An evaluation unit 7033 is used to evaluate the trained model and adjust the model parameters until a predetermined evaluation standard is met; The determination unit 7034 is used to determine the trained network point operation evaluation model.

[0043] This embodiment uses feature data sets and historical operation data to train models, which can more accurately evaluate the operating conditions of outlets and provide reliable results; by continuously adjusting model parameters and retraining, the performance of the model can be continuously improved to make it better adapt to the ever-changing operating environment.

[0044] In some embodiments, the evaluation module 704 is used to input the historical operation data of the express outlets into the outlet operation evaluation model to output an outlet operation evaluation result; In some embodiments, the evaluation module 704 includes: The first preset unit 7041 is used to preset the health level of the express outlet operation and the threshold of the health level; The output unit 7042 is used to input the historical operation data of the express outlet into the outlet operation evaluation model, and output the operation evaluation result of the express outlet; The judgment unit 7043 is used to compare the operation evaluation result with the threshold of the health level, and judge the health level of the express outlet operation according to the comparison result, and the health level includes at least healthy, sub-healthy, unhealthy and other categories.

[0045] The evaluation results output by the embodiment of the present invention provide the management with a detailed basis for operation analysis, making the operation decision-making process more scientific and reliable, and facilitating the formulation of more targeted operation management measures.

[0046] In some embodiments, the adjustment module 705 is used to adjust relevant parameters of the network operation evaluation model based on the evaluation result.

[0047] In some embodiments, the adjustment module 705 includes: The second preset unit 7051 is used to preset the evaluation criteria for the express delivery outlet operation; The second analysis unit 7052 is used to analyze the evaluation results of the express delivery point operation and determine the deviation of the evaluation model during the evaluation process; An adjusting unit 7053, configured to adjust relevant parameters of the network point operation evaluation model according to the deviation; The repeating unit 7054 is used to repeat the above steps until the model evaluation result meets the preset evaluation standard.

[0048] The embodiments of the present invention can improve the prediction accuracy of the model by adjusting the model parameters, making the evaluation results more accurate and better reflecting the actual operating conditions of the outlets; adjusting the parameters can reduce the possibility of model misjudgment, improve the credibility of the evaluation results, and reduce losses caused by evaluation errors.

[0049] In some embodiments, adjusting relevant parameters of the network point operation evaluation model based on the evaluation result includes: Furthermore, adjusting the relevant parameters of the network point operation evaluation model based on the evaluation result also includes: Obtain the health level assessment results of the express delivery outlet operations; Determining the health level of the express delivery outlet operation according to the health level assessment result; According to the health level of the express outlets, potential franchise areas around the express outlets are matched; According to the health level of the express delivery outlets, corresponding management strategies and resource allocation plans are planned for the franchise intention area, and the plans at least include increasing personnel and equipment investment and optimizing work flow measures.

[0050] The embodiment of the present invention can find the corresponding franchise intention area according to the evaluation results. For healthy outlets, maintain the existing resource configuration and perform light optimization. For sub-healthy outlets, analyze their existing problems, such as insufficient staff or aging equipment, and increase staff recruitment plans or arrange equipment updates accordingly. For unhealthy outlets, conduct a comprehensive diagnosis and formulate detailed improvement plans, including substantial investment in personnel and equipment, as well as in-depth optimization of work processes.

[0051] above Figure 7 and Figure 8 The express delivery outlet operation evaluation method in the embodiment of the present invention is described in detail from the perspective of modular functional entities, and the electronic device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0052] Fig. 9 8 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 800 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 810 (for example, one or more processors) and a memory 820, and one or more storage media 830 (for example, one or more mass storage devices) storing application programs 833 or data 832. Among them, the memory 820 and the storage medium 830 can be temporary storage or permanent storage. The program stored in the storage medium 830 may include one or more modules (not shown in the figure) for vehicle dispatching at a distribution center, and each module may include a series of instruction operations in the electronic device 800. Furthermore, the processor 810 may be configured to communicate with the storage medium 830 to execute a series of instruction operations in the storage medium 830 on the electronic device 800.

[0053] The electronic device 800 may also include one or more power supplies 840, one or more wired or wireless network interfaces 850, one or more input and output interfaces 850, and / or one or more operating systems 831, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Fig. 9 The structure of the electronic device shown does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.

[0054] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the distribution center vehicle dispatching method.

[0055] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0056] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0057] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the operation of express delivery outlets, characterized in that: The method comprises: Acquire express outlet operation data, which is used to obtain a set of factors affecting express outlet operation evaluation and express outlet historical operation data; Determining a feature data set based on a set of evaluation factors affecting the express delivery outlet operations; Build a branch operation evaluation model, use the feature data set and branch historical operation data to train the branch operation evaluation model, and determine the trained branch operation evaluation model; Inputting the historical operation data of the express delivery outlets into the outlet operation evaluation model to output the outlet operation evaluation results; Based on the evaluation results, relevant parameters of the network point operation evaluation model are adjusted.

2. The express delivery outlet operation evaluation method according to claim 1, characterized in that: The obtaining of express outlet operation data is used to obtain a set of evaluation factors affecting express outlet operation and express outlet historical operation data, including: Analyze the business process of the express outlet operation, determine the factors affecting the express outlet operation evaluation, and obtain the set of factors affecting the express outlet operation evaluation formed by the factors; By connecting to the database system of the express delivery outlet, the historical operation data of the express delivery outlet is obtained; Using a data cleaning algorithm, the historical operating data of the express delivery outlets is standardized and converted into a unified format.

3. The express delivery outlet operation evaluation method according to claim 1, characterized in that: Determining the feature data set according to the set of factors affecting the express outlet operation evaluation includes: Analyze the factors in the set of factors affecting the express delivery outlet operation evaluation to determine the degree of their influence on the express delivery outlet operation evaluation; Selecting factors that have a significant impact on the express outlet operation evaluation from the factor set as feature variables, and quantifying the feature variables to obtain quantified feature data; The quantified feature data are combined into a feature data set.

4. The express delivery outlet operation evaluation method according to claim 3, characterized in that: The step of building a network point operation evaluation model, training the network point operation evaluation model using a feature data set and historical network point operation data, and determining the trained network point operation evaluation model includes: Selecting a suitable learning algorithm according to the feature data set and the historical operation data; Using the feature data set and the historical operation data as input to train the model; Evaluate the trained model and adjust the model parameters until the predetermined evaluation criteria are met; Determine the trained outlet operation evaluation model.

5. The express delivery outlet operation evaluation method according to claim 2, characterized in that: The step of inputting the historical operation data of the express outlets into the outlet operation evaluation model to output an outlet operation evaluation result includes: Presetting the health level and health level threshold of the express delivery outlet operation; Inputting the historical operation data of the express outlets into the outlet operation evaluation model, and outputting the operation evaluation results of the express outlets; The operation evaluation result is compared with the threshold value of the health level, and the health level of the express outlet operation is determined based on the comparison result, and the health level includes at least healthy, sub-healthy, unhealthy and other categories.

6. The express delivery outlet operation evaluation method according to claim 5, characterized in that: The adjusting relevant parameters of the network point operation evaluation model based on the evaluation result includes: Preset evaluation criteria for the operation of the express delivery outlets; Analyze the evaluation results of the express delivery outlet operations and determine the deviation of the evaluation model during the evaluation process; Adjust relevant parameters of the network point operation evaluation model according to the deviation; Repeat the above steps until the model evaluation results meet the preset evaluation criteria.

7. The express delivery outlet operation evaluation method according to claim 6, characterized in that: The adjusting relevant parameters of the network point operation evaluation model based on the evaluation result also includes: Obtain the health level assessment results of the express delivery outlet operations; Determining the health level of the express delivery outlet operation according to the health level assessment result; According to the health level of the express outlets, potential franchise areas around the express outlets are matched; According to the health level of the express delivery outlets, corresponding management strategies and resource allocation plans are planned for the franchise intention area, and the plans at least include increasing personnel and equipment investment and optimizing work flow measures.

8. A courier outlet operation evaluation device, characterized in that: include: The module for obtaining express outlet operation data is used to obtain the set of factors affecting express outlet operation evaluation and the historical operation data of express outlets; A feature data set determination module, used to determine a feature data set according to a set of factors affecting the express outlet operation evaluation; Build an outlet operation evaluation model module to train the outlet operation evaluation model using feature data sets and outlet historical operation data, and determine the trained outlet operation evaluation model; An evaluation module, used to input the historical operation data of the express outlets into the outlet operation evaluation model to output an outlet operation evaluation result; An adjustment module is used to adjust relevant parameters of the network point operation evaluation model based on the evaluation result.

9. A computer device, characterized in that: The computer device includes a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory so that the computer device executes the express delivery point operation evaluation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is loaded by a processor to execute the express delivery outlet operation evaluation method described in any one of claims 1-7.

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