Branch account recharging management method, device and equipment and storage medium

Abstract

The invention relates to the field of logistics, and discloses a website account recharging management method, device and equipment and a storage medium, and the method is used for carrying out signing management on a logistics website and predicting the monthly pre-charging amount of the logistics website. The method comprises the following steps: when a signing state of a logistics network is unsigned, verifying basic information of the logistics network, and generating a signing request according to the basic information passing the verification; respectively putting the logistics network points into a first network point set and a second network point set based on a signing result; for the logistics network points in the first network point set, updating the signing request based on the reason of signing failure, and when the signing result of the logistics network points is that signing succeeds, moving the logistics network points from the first network point set to a second network point set; and for the logistics network points in the second network point set, predicting the monthly pre-charging amount of the to-be-predicted month by using a recharging amount prediction model based on the BP neural network, and feeding back the monthly pre-charging amount to the logistics network points.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to a method, device, equipment and storage medium for managing network account recharge. Background Art

[0002] In the context of the current booming express delivery industry, the mechanism for distributing courier commissions is gradually transforming towards a more efficient, transparent and compliant direction. Traditionally, the distribution of courier commissions usually consists of two parts: one part is paid directly to the courier's personal account through the direct delivery of commissions, using a flexible employment model. This method has the characteristics of high flexibility and fast response, which effectively improves the efficiency of capital circulation and the work enthusiasm of couriers; the other part is distributed by each outlet, which often faces challenges such as cumbersome procedures, difficult fund supervision and complex tax processing in actual operations.

[0003] In view of this, in order to comprehensively optimize the commission payment process at the outlets, ensure the online and transparent flow of funds, and effectively solve the problem of tax invoicing, the company has developed and launched the "Outlet Flexible Work System" internally. As an integrated digital management tool, the system aims to provide express delivery outlets with a one-stop, intelligent commission payment and tax management solution.

[0004] When managing their recharge funds, logistics outlets need to carefully balance two considerations: one is the balance between fund liquidity and utilization efficiency, and the other is the guarantee of service stability and user experience.

[0005] On the one hand, if logistics outlets recharge too much funds into the outlets' flexible worker system accounts, although this may seem to ensure the continuity and stability of services, it may actually lead to a large amount of overall capital being occupied by the enterprise. This capital occupation will limit the investment and development of the enterprise in other areas or projects, and reduce the efficiency of capital utilization.

[0006] On the other hand, if the branch account does not have sufficient funds, the courier's commission may not be paid in time. If the commission is not paid in time or is insufficient, the courier may feel dissatisfied and disappointed, which will not only affect their work enthusiasm and service quality, but may also lead to staff turnover and recruitment difficulties.

[0007] Therefore, the existing technology still needs to be improved and developed. Summary of the invention

[0008] The present invention provides a method, device, equipment and storage medium for managing network account recharge, which are used for contract management of logistics network and prediction of monthly pre-charge amount of logistics network.

[0009] The first aspect of the present invention provides a method for managing the recharge of an account at an outlet, the method comprising: determining whether the contract status of a logistics outlet is unsigned, and if so, obtaining basic information of the logistics outlet; verifying the basic information of the logistics outlet, and generating a contract request based on the verified basic information; obtaining a contract result corresponding to the contract request based on the contract request, placing the logistics outlets with a contract failure result into a first outlet set, and placing the logistics outlets with a contract success result into a second outlet set; for the logistics outlets in the first outlet set, obtaining the reason for the contract failure of the logistics outlet, and updating the contract request based on the reason for the contract failure, and when the contract result of the logistics outlet is a contract success, moving the logistics outlet from the first outlet set to the second outlet set; for the logistics outlets in the second outlet set, obtaining historical recharge information of the logistics outlet, and based on the historical recharge information, using a recharge amount prediction model based on a BP neural network to predict the monthly precharge amount of the predicted month, and feeding back the monthly precharge amount to the logistics outlet.

[0010] Optionally, in a first implementation method of the first aspect of the present invention, the judgment of whether the contract status of the logistics outlet is uncontracted, and if so, obtaining the basic information of the logistics outlet, includes: obtaining the identification code of the logistics outlet, and querying the contract status value of the logistics outlet based on the identification code using a SQL statement; comparing the contract status value with a preset uncontracted status value, if the two are consistent, determining that the contract status of the logistics outlet is uncontracted; if the contract status of the logistics outlet is uncontracted, obtaining the basic information of the logistics outlet.

[0011] Optionally, in a second implementation method of the first aspect of the present invention, the basic information of the logistics outlets is verified, and a signing request is generated based on the verified basic information, including: parsing the basic information of the logistics outlets into multiple fields, and matching the multiple fields with a preset field list. If the match is successful, it is determined that the basic information verification has passed; calling a preset signing request template, and filling the verified basic information into the default parameters of the signing request template; and generating a signing request based on the filled signing request template.

[0012] Optionally, in a third implementation method of the first aspect of the present invention, obtaining a signing result corresponding to the signing request according to the signing request, putting the logistics outlets with a signing result of failed signing into a first outlet set, and putting the logistics outlets with a signing result of successful signing into a second outlet set, includes: obtaining a signing record according to an identification code corresponding to the logistics outlet in the signing request, and analyzing the signing record to obtain a signing result, the signing result including a successful signing and a failed signing; constructing two blank sets, respectively as the first outlet set and the second outlet set; if the signing result corresponding to the logistics outlet is a failed signing, the logistics outlet is put into the first outlet set, and if the signing result corresponding to the logistics outlet is a successful signing, the logistics outlet is put into the second outlet set.

[0013] Optionally, in a fourth implementation method of the first aspect of the present invention, for the logistics outlets in the first outlet set, the reason for the failure to sign the contract at the logistics outlets is obtained, and the signing request is updated based on the reason for the failure to sign the contract, and when the signing result of the logistics outlet is a successful signing, the logistics outlets are moved from the first outlet set to the second outlet set, including: for the logistics outlets in the first outlet set, obtaining the signing record according to the identification code corresponding to the logistics outlet; analyzing the signing record to obtain the reason for the failure to sign the contract at the logistics outlet, and updating the signing request based on the reason for the failure to sign the contract; when the signing result of the logistics outlet is a successful signing, removing the corresponding logistics outlet from the first outlet set and placing it in the second outlet set.

[0014] Optionally, in a fifth implementation of the first aspect of the present invention, for the logistics outlets in the second outlet set, historical recharge information of the logistics outlets is obtained, and based on the historical recharge information, a recharge amount prediction model based on a BP neural network is used to predict the monthly pre-charge amount of the month to be predicted, and the monthly pre-charge amount is fed back to the logistics outlets, including: constructing a recharge amount prediction model based on the BP neural network; for the logistics outlets in the second outlet set, historical recharge information of the logistics outlets is obtained, and the historical recharge information includes historical recharge amounts and corresponding recharge times; basic prediction information related to the month to be predicted is filtered out from the historical recharge information, and the prediction basic information is input into the recharge amount prediction model to obtain the monthly pre-charge amount of the month to be predicted, and the monthly pre-charge amount is fed back to the logistics outlets, and the prediction basic information includes at least the recharge amounts and corresponding recharge times of historical months adjacent to the prediction month.

[0015] Optionally, in a sixth implementation method of the first aspect of the present invention, the recharge amount prediction model is constructed based on the BP neural network, including: collecting historical recharge amounts and corresponding recharge times of different logistics outlets as samples; performing data enhancement on the samples to obtain an enhanced sample data set, and dividing the enhanced sample data set into a training set and a test set; using the training set to train the pre-trained BP neural network, and using the test set to tune the trained BP neural network to obtain a recharge amount prediction model.

[0016] The second aspect of the present invention provides a network point account recharge management device, including: a judgment module, used to judge whether the contract status of the logistics network point is unsigned, and if so, obtain the basic information of the logistics network point; a generation module, used to verify the basic information of the logistics network point, and generate a contract request based on the verified basic information; a division module, used to obtain the contract result corresponding to the contract request according to the contract request, put the logistics network point with a contract failure result into a first network point set, and put the logistics network point with a contract success result into a second network point set; an update module, used to obtain the reason for the contract failure of the logistics network point in the first network point set, and update the contract request based on the reason for the contract failure, when the contract result of the logistics network point is a contract success, move the logistics network point from the first network point set to the second network point set; a prediction module, used to obtain the historical recharge information of the logistics network point in the second network point set, and use the recharge amount prediction model based on the BP neural network to predict the monthly precharge amount of the predicted month according to the historical recharge information, and feed back the monthly precharge amount to the logistics network point.

[0017] Optionally, in a first implementation method of the second aspect of the present invention, the judgment module includes: a first query unit, used to obtain an identification code of the logistics outlet, and use a SQL statement to query the contract status value of the logistics outlet based on the identification code; a comparison unit, used to compare the contract status value with a preset uncontracted status value, and if the two are consistent, it is determined that the contract status of the logistics outlet is uncontracted; a first acquisition unit, used to obtain basic information of the logistics outlet when the contract status of the logistics outlet is uncontracted.

[0018] Optionally, in a second implementation method of the second aspect of the present invention, the generation module includes: a parsing unit, used to parse the basic information of the logistics outlets into multiple fields, and match the multiple fields with a preset field list. If the match is successful, it is determined that the basic information verification has passed; a filling unit, used to call a preset signing request template, and fill the verified basic information into the default parameters of the signing request template; a generation unit, used to generate a signing request based on the filled signing request template.

[0019] Optionally, in a third implementation method of the second aspect of the present invention, the division module includes: a second query unit, used to query the contract record according to the identification code corresponding to the logistics outlet in the contract request, and analyze the contract record to obtain the contract result, the contract result including successful contract and failed contract; a first construction unit, used to construct two blank sets, respectively as the first outlet set and the second outlet set; a division unit, used to put the logistics outlet into the first outlet set when the contract result corresponding to the logistics outlet is a failed contract, and put the logistics outlet into the second outlet set when the contract result corresponding to the logistics outlet is a successful contract.

[0020] Optionally, in a fourth implementation method of the second aspect of the present invention, the update module includes: a third query unit, used to query the contract record for the logistics outlets in the first outlet set according to the identification code corresponding to the logistics outlets; an analysis unit, used to analyze the contract record to obtain the reason for the contract failure of the logistics outlet, and update the contract request based on the reason for the contract failure; an update unit, used to remove the corresponding logistics outlet from the first outlet set and put it into the second outlet set when the contract result of the logistics outlet is a successful contract.

[0021] Optionally, in a fifth implementation of the second aspect of the present invention, the prediction module includes: a second construction unit, used to construct a recharge amount prediction model based on a BP neural network; a second acquisition unit, used to obtain historical recharge information of the logistics outlets in the second outlet set, the historical recharge information including historical recharge amounts and corresponding recharge times; a prediction unit, used to filter out prediction basic information related to the month to be predicted from the historical recharge information, and input the prediction basic information into the recharge amount prediction model to obtain the monthly precharge amount of the month to be predicted, and feed back the monthly precharge amount to the logistics outlets.

[0022] The third aspect of the present invention provides a branch account recharge management device, comprising: a memory and at least one processor, the memory storing computer-readable instructions, the memory and the at least one processor being interconnected via a line; the at least one processor calling the computer-readable instructions in the memory so that the branch account recharge management device executes each step of the branch account recharge management method as described above.

[0023] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, which, when executed on a computer, enable the computer to execute the various steps of the above-mentioned method for managing branch account recharge.

[0024] In the technical solution provided by the present invention, when it is determined that the contract status of a logistics outlet is not signed, the basic information of the logistics outlet is obtained, the basic information of the logistics outlet is verified, and a contract request is generated based on the verified basic information, and the logistics outlets are distinguished as a set of outlets with successful and failed contracts based on the contract results, thereby realizing dynamic management and tracking of the outlet status, and repeatedly analyzing and optimizing the outlets with failed contracts until the contract is successfully signed, thereby enhancing the flexibility and adaptability of the contract process. In addition, the BP neural network prediction model is used to provide the outlets with a monthly precharge amount, which can provide relatively accurate prediction results based on historical data and current trends, and help the outlets to carry out more scientific financial planning and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A first flow chart of the method for managing branch account recharge provided by an embodiment of the present invention;

[0026] Figure 2 A second flow chart of the method for managing branch account recharge provided by an embodiment of the present invention;

[0027] Figure 3 A third flow chart of the method for managing branch account recharge provided by an embodiment of the present invention;

[0028] Figure 4 A fourth flow chart of the method for managing branch account recharge provided by an embodiment of the present invention;

[0029] Figure 5 A fifth flow chart of the method for managing branch account recharge provided by an embodiment of the present invention;

[0030] Figure 6 A sixth flow chart of the method for managing branch account recharge provided by an embodiment of the present invention;

[0031] Figure 7 A schematic diagram of the structure of a network account recharge management device provided by an embodiment of the present invention;

[0032] Figure 8 A schematic diagram of the structure of a branch account recharge management device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The embodiment of the present invention provides a method, device, equipment and storage medium for managing the recharge of a network point account, and the method is used for contract management of a logistics network point and predicting the monthly precharge amount of the logistics network point. The method includes: determining whether the contract status of the logistics network point is unsigned, and if so, obtaining the basic information of the logistics network point; verifying the basic information of the logistics network point, and generating a contract request according to the verified basic information; obtaining the contract result corresponding to the contract request according to the contract request, putting the logistics network point with a contract failure result into a first network point set, and putting the logistics network point with a contract success result into a second network point set; for the logistics network points in the first network point set, obtaining the reason for the contract failure of the logistics network point, and updating the contract request based on the reason for the contract failure, and when the contract result of the logistics network point is a contract success, moving the logistics network point from the first network point set to the second network point set; for the logistics network points in the second network point set, obtaining the historical recharge information of the logistics network point, and according to the historical recharge information, using the recharge amount prediction model based on the BP neural network to predict the monthly precharge amount of the predicted month, and feeding back the monthly precharge amount to the logistics network point.

[0034] 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.

[0035] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 A first embodiment of a method for managing a network account recharge in an embodiment of the present invention includes:

[0036] S101. Determine whether the contract status of the logistics outlet is unsigned. If so, obtain basic information of the logistics outlet.

[0037] It is understandable that the execution subject of the present invention may be a network account recharge management device, or a terminal or a server, which is not limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0038] In this embodiment, the contract status information of the logistics network point is obtained by querying the database or calling the relevant API.

[0039] In this embodiment, if the contract status of the logistics outlet is not signed, the basic information of the logistics outlet is retrieved from the database. The basic information includes a photo of the business license, the company registration name, the unified social credit code, the company registration address, the legal person's name, the legal person's mobile phone number, the legal person's ID number, the contact person's name, the legal person's mobile phone number and the legal person's ID number.

[0040] S102: Verify the basic information of the logistics outlets, and generate a contract signing request based on the verified basic information.

[0041] In this embodiment, the basic information of the logistics network point is checked for integrity. When the basic information of the logistics network point is checked for integrity, the fields that the basic information needs to include usually cover the key data required for the operation of the logistics network point.

[0042] In this embodiment, a preset rule or algorithm may also be used to perform format verification and non-empty verification on the basic information.

[0043] In this embodiment, the contract signing request includes not only the basic information of the logistics outlets, but also a description of the fund disbursement scenario and a service fee rate.

[0044] S103. Obtain a signing result corresponding to the signing request according to the signing request, add the logistics outlets with a signing result of failed signing to the first outlet set, and add the logistics outlets with a signing result of successful signing to the second outlet set.

[0045] In this embodiment, after the server generates a contract signing request, it sends the contract signing request to the corresponding logistics outlet, and the logistics outlet signs the contract and feeds back the contract signing result, which includes a successful contract signing and a failed contract signing.

[0046] In this embodiment, the subsequent processing of logistics outlets with successful and failed contract signing is different. Therefore, it is necessary to construct a first outlet set and a second outlet set, put the logistics outlets with failed contract signing results into the first outlet set, and put the logistics outlets with successful contract signing results into the second outlet set.

[0047] S104. For the logistics outlets in the first outlet set, repeatedly analyze the reasons for the contract signing failure and generate a new contract signing request based on the analysis results until the contract signing result of the logistics outlet is a successful contract signing. When the contract signing result of the logistics outlet is a successful contract signing, move the logistics outlet from the first outlet set to the second outlet set.

[0048] In this embodiment, the contract signing request is sent to the corresponding logistics outlet. During the contract signing process of the logistics outlet, a contract signing record is generated. The contract signing record of the logistics outlet where the contract signing fails includes the contract signing result and the relevant description of the contract signing failure. For example, the contract signing failure description is as follows:

[0049] Information does not match: During system verification, it was found that the unified social credit code provided is inconsistent with the record in the industrial and commercial registration information database. Please check and resubmit the correct unified social credit code.

[0050] Missing qualification documents: The required scanned copy of the logistics business license is not included in the contract materials submitted. According to our company's regulations, all logistics outlets must hold a valid logistics business license before signing. Please complete the qualification documents as soon as possible and resubmit.

[0051] Bank account verification failed: When trying to verify the bank account information provided, it was found that the account status was abnormal (such as cancelled, frozen, etc.), resulting in the inability to continue the contract signing process. Please confirm the validity of the bank account and update the correct account information before applying again.

[0052] S105. For the logistics outlets in the second outlet set, the historical recharge information of the logistics outlets is obtained, and according to the historical recharge information, the recharge amount prediction model based on the BP neural network is used to predict the predicted monthly precharge amount of the logistics outlets, and the predicted monthly precharge amount of the logistics outlets is fed back to the logistics outlets.

[0053] In this embodiment, the recharge information corresponding to the logistics outlet is retrieved from the database, including the account balance, historical recharge records, etc.

[0054] In this embodiment, BP neural network, namely back propagation neural network (Backpropagation Neural Network), is a multi-layer feedforward neural network based on error back propagation algorithm. BP neural network consists of input layer, hidden layer (can have multiple) and output layer. Each neuron (or node, unit) is connected to all neurons in the previous layer, transmits signals by weighted sum, and undergoes nonlinear transformation through activation function.

[0055] In this embodiment, the prediction results are fed back to the logistics outlets in a timely manner, which enhances the transparency of information and the responsiveness of the outlets.

[0056] The present embodiment provides a method for managing branch account recharge, which, when determining that the contract status of a logistics branch is not signed, obtains basic information of the logistics branch, verifies the basic information of the logistics branch, generates a contract request based on the verified basic information, and distinguishes the logistics branch into a set of branches with successful and failed contracts based on the contract results, thereby realizing dynamic management and tracking of branch status, and repeatedly analyzing and optimizing the branches with failed contracts until the contract is successfully signed, thereby enhancing the flexibility and adaptability of the contract process. In addition, the BP neural network prediction model is used to provide the branch with a monthly precharge amount, which can provide relatively accurate prediction results based on historical data and current trends, and help the branch to carry out more scientific fund planning and management.

[0057] See also Figure 2 The second embodiment of the method for managing the recharge of a network account in the embodiment of the present invention includes:

[0058] S201. Obtain the identification code of the logistics network point, and query the contract status value of the logistics network point using a SQL statement based on the identification code.

[0059] In this embodiment, an SQL query statement is constructed, the identification code is used as the query condition, the contract status value of the logistics network point is retrieved from the database, the SQL statement is executed, and the contract status value is obtained from the result returned by the database.

[0060] S202: Compare the contracted status value with the preset uncontracted status value. If the two are consistent, the contracted status of the logistics network point is determined to be uncontracted.

[0061] In this embodiment, a value indicating the "unsigned" state (such as 0, 'unsigned', etc.) is preset in the system for comparison with the queried contract status value. The queried contract status value is compared with the preset unsigned state value to determine whether the two are consistent. If the contract status value is consistent with the preset unsigned state value, then it can be determined that the contract status of the logistics network is unsigned.

[0062] S203. If the contract signing status of the logistics outlet is not signed, obtain basic information of the logistics outlet.

[0063] In this embodiment, once it is determined that the contract signing status of the logistics network point is not signed, the next step can be performed: obtaining basic information of the logistics network point.

[0064] The acquisition of basic information can be achieved through SQL query, constructing one or more query statements to retrieve relevant information of logistics outlets (such as company name, legal representative, contact information, business address, etc.).

[0065] These query statements are executed, and the query results (i.e., basic information of logistics outlets) are returned to the server for subsequent processing.

[0066] In this embodiment, the identification code of the logistics outlet is obtained, and the contract status value of the logistics outlet is queried based on the identification code using a SQL statement. The contract status value is compared with the preset uncontracted status value. If the two are consistent, the contract status of the logistics outlet is determined to be uncontracted. When the contract status of the logistics outlet is uncontracted, the basic information of the logistics outlet is obtained. Through database query and simple logical judgment, the contract status of the logistics outlet can be quickly determined, reducing manual intervention and improving processing efficiency.

[0067] See also Figure 3 A third embodiment of a method for managing a network account recharge in an embodiment of the present invention includes:

[0068] S301. Parse the basic information of the logistics outlets into multiple fields, and match the multiple fields with a preset field list. If the match is successful, it is determined that the basic information verification has passed.

[0069] In this embodiment, a preset field list is defined, which includes all necessary fields and their data types, formats, etc. The parsed fields are matched with the preset field list one by one to check whether all necessary fields exist and whether their types, formats, etc. meet the requirements. If all fields are matched successfully, it is determined that the basic information verification has passed; otherwise, the unmatched fields are recorded and an error message is returned.

[0070] S302: Call the preset contract signing request template and fill the verified basic information into the default parameters of the contract signing request template.

[0071] In this embodiment, the default parameter placeholders in the contract signing request template are traversed. For each placeholder, the corresponding field value is found in the verified basic information according to its name or identifier. The found field value is filled into the corresponding placeholder position, replacing the original placeholder text.

[0072] S303: Generate a signing request according to the filled signing request template.

[0073] In this embodiment, after all default parameter placeholders are correctly filled, the filled template is converted into the final signing request format (such as JSON, XML, etc.), that is, the final signing request document or data structure is generated as the signing request.

[0074] In this embodiment, the generated contract signing request includes all necessary logistics network information and contract signing terms, and can be directly used in the subsequent contract signing process.

[0075] In this embodiment, the basic information of the logistics outlets is parsed into multiple fields, and the multiple fields are matched with a preset field list. If the match is successful, the basic information is determined to have passed the verification, and then the preset signing request template is called, and the verified basic information is filled into the default parameters of the signing request template. Finally, a signing request is generated according to the filled-in signing request template. Through field matching and template filling, the accuracy and consistency of the basic information are ensured, the efficiency of generating signing requests is improved, and the processing time is shortened.

[0076] See also Figure 4 A fourth embodiment of a method for managing a network account recharge in an embodiment of the present invention includes:

[0077] S401. Query the contract record according to the identification code corresponding to the logistics outlet in the contract request, and analyze the contract record to obtain the contract result, which includes a contract success or a contract failure.

[0078] In this embodiment, each logistics network point is provided with a corresponding identification code, and the corresponding contract record in the database can be queried according to its corresponding identification code.

[0079] In this embodiment, the contract signing record includes a contract signing situation description and a contract signing result. For example, the contract signing description of a logistics network point where a contract signing fails includes the reason for the contract signing failure.

[0080] In this embodiment, the contract signing result corresponding to the logistics network point can be obtained through a keyword matching algorithm.

[0081] S402: Construct two blank sets, which are used as the first network point set and the second network point set respectively.

[0082] In this embodiment, two blank sets are constructed in the preset database, which are used to store the logistics outlets with failed contracts (the first outlet set) and the logistics outlets with successful contracts (the second outlet set).

[0083] S403. If the contract signing result corresponding to the logistics network point is a contract signing failure, the logistics network point is placed in the first network point set; if the contract signing result corresponding to the logistics network point is a contract signing success, the logistics network point is placed in the second network point set.

[0084] In this embodiment, for example, if the contract signing result of logistics network A is a contract signing failure, logistics network A is placed in the first network set. For another example, if the contract signing result of logistics network B is a contract signing success, logistics network A is placed in the second network set.

[0085] In this embodiment, while the logistics outlets are stored in the collection, the contract status of each outlet is recorded and marked to facilitate subsequent processing.

[0086] In this embodiment, for outlets where no contract record can be found or the contract status is unclear, exception processing is performed, such as re-examining the contract request or contacting the outlet to confirm the information.

[0087] In this embodiment, the contract signing record is obtained by querying the identification code corresponding to the logistics outlet in the contract signing request, and the contract signing record is analyzed to obtain the contract signing result. By dividing the contract signing results into two categories, success and failure, it is convenient to carry out targeted processing of outlets with different results.

[0088] See also Figure 5 A fifth embodiment of a method for managing a network account recharge in an embodiment of the present invention includes:

[0089] S501. For a logistics outlet in the first outlet set, obtain a contract signing record according to an identification code corresponding to the logistics outlet.

[0090] In this embodiment, the unique identification code (such as ID, code, etc.) of the logistics network point is used as a query condition to retrieve all the contract records of the network point in the database.

[0091] S502: Analyze the contract signing record to obtain the reason for the contract signing failure, and update the contract signing request based on the reason for the contract signing failure.

[0092] In this embodiment, the failure reason field in the failure record is analyzed, and possible reasons include but are not limited to: incomplete information, inconsistent terms, system errors, etc. If the information is incomplete, new information is obtained, and the contract signing request is updated according to the new information. If the logistics network fails to sign the contract again, the steps of analyzing the contract signing record to obtain the reason for the contract signing failure and updating the contract signing request based on the reason for the contract signing failure are repeated until the contract signing result of the logistics network is a successful contract signing.

[0093] S503. When the contract signing result of the logistics network point is successful, the corresponding logistics network point is removed from the first network point set and placed in the second network point set.

[0094] In this embodiment, when the signing result of the logistics outlet is a successful signing, the signing status of the logistics outlet in the database is updated to "successful", and the record of the logistics outlet is removed from the first outlet set (the set to be signed or the set under signing), and the record of the logistics outlet is added to the second outlet set (the set that has signed the contract).

[0095] In this embodiment, by analyzing the reasons for the contract signing failure and updating the contract signing request, the processing efficiency and accuracy are improved, and the strategy is adjusted according to the specific reasons for each contract signing failure, which increases the possibility of successful contract signing and avoids blind retries. In addition, when the contract signing result of the logistics outlet is a successful contract signing, the corresponding logistics outlet is removed from the first outlet set and placed in the second outlet set to effectively manage the contract signing status of the logistics outlets and facilitate the centralized resource processing of the remaining unsigned outlets.

[0096] See also Figure 6 A sixth embodiment of a method for managing a network account recharge in an embodiment of the present invention includes:

[0097] S601. Construct a recharge amount prediction model based on BP neural network.

[0098] In this embodiment, a recharge amount prediction model is constructed based on the BP neural network, which specifically includes: collecting historical recharge amounts and corresponding recharge times of different logistics outlets as samples; performing data enhancement on the samples to obtain an enhanced sample data set, and dividing the enhanced sample data set into a training set and a test set; using the training set to train the pre-trained BP neural network, and using the test set to tune the trained BP neural network to obtain a recharge amount prediction model.

[0099] In this embodiment, when the historical recharge amounts and corresponding recharge times of different logistics outlets are collected as samples, the collected data are cleaned, including removing outliers, duplicate records, etc., to ensure data quality.

[0100] In this embodiment, more samples can be generated through time series analysis (such as interpolation, smoothing, etc.), or similar but different data can be generated through simulation, so as to achieve data enhancement of the samples and obtain an enhanced sample data set.

[0101] In this embodiment, the BP neural network is trained using the training set data, and the network weights and biases are adjusted using a back propagation algorithm.

[0102] S602: For a logistics outlet in the second outlet set, obtain historical recharge information of the logistics outlet, where the historical recharge information includes a historical recharge amount and a corresponding recharge time.

[0103] In this embodiment, the recharge information corresponding to the logistics network point can be extracted from the recharge record of the logistics network point. If there is no recharge record for the logistics network point, the historical expenditure and expenditure time of the logistics network point on the courier commission can be collected.

[0104] S603. Filter out the forecast basic information related to the month to be forecasted from the historical recharge information, input the forecast basic information into the recharge amount forecast model to obtain the monthly pre-charge amount of the month to be forecasted, and feed back the monthly pre-charge amount to the logistics outlets.

[0105] In this embodiment, the prediction basic information at least includes the recharge amount and the corresponding recharge time of the historical months adjacent to the prediction month.

[0106] Furthermore, the forecast basic information may also include the recharge amount and the recharge time corresponding to the recharge amount in the same month of previous years. For example, if the monthly pre-charge amount of a logistics outlet in July needs to be forecasted, the forecast basic information may include the recharge amount and the corresponding recharge time in May and June of the same year and July of previous years.

[0107] In this embodiment, a recharge amount prediction model can be set to predict the monthly pre-charge amount of the logistics outlets in the next month or the next three months, and the specific prediction period can be adjusted according to actual conditions.

[0108] In this embodiment, the monthly pre-charge amount of the logistics outlets is automatically predicted by the recharge amount prediction model constructed based on the BP neural network, so that the enterprise can make more reasonable capital arrangements and budget planning based on the data and reduce the uncertainty caused by human judgment.

[0109] The above describes the method for managing the recharge of a branch account in an embodiment of the present invention. The following describes the device in an embodiment of the present invention. Figure 7 , the implementation of the network account recharge management device in the embodiment of the present invention includes:

[0110] The judgment module 701 is used to judge whether the contract status of the logistics network point is unsigned, and if so, obtain the basic information of the logistics network point;

[0111] A generating module 702 is used to verify the basic information of the logistics outlets and generate a contract signing request according to the verified basic information;

[0112] A division module 703 is used to obtain a contract result corresponding to the contract request according to the contract request, put the logistics outlets with a contract failure result into a first outlet set, and put the logistics outlets with a contract success result into a second outlet set;

[0113] An updating module 704 is used to obtain the reason why the contract signing of the logistics outlets in the first outlet set fails, and update the contract signing request based on the reason why the contract signing fails. When the contract signing result of the logistics outlet is successful, the logistics outlet is moved from the first outlet set to the second outlet set;

[0114] The prediction module 705 is used to obtain the historical recharge information of the logistics outlets in the second outlet set, and according to the historical recharge information, use the recharge amount prediction model based on the BP neural network to predict the monthly pre-charge amount of the predicted month, and feed back the monthly pre-charge amount to the logistics outlets.

[0115] In this embodiment, the judgment module 701 includes: a first query unit 7011, used to obtain the identification code of the logistics outlet, and use a SQL statement to query the contract status value of the logistics outlet based on the identification code; a comparison unit 7012, used to compare the contract status value with a preset uncontracted status value. If the two are consistent, it is determined that the contract status of the logistics outlet is uncontracted; a first acquisition unit 7013, used to obtain the basic information of the logistics outlet when the contract status of the logistics outlet is uncontracted.

[0116] In this embodiment, the generation module 702 includes: a parsing unit 7021, which is used to parse the basic information of the logistics network into multiple fields, and match the multiple fields with a preset field list. If the match is successful, it is determined that the basic information verification has passed; a filling unit 7022, which is used to call a preset signing request template and fill the verified basic information into the default parameters of the signing request template; a generation unit 7023, which is used to generate a signing request according to the filled signing request template.

[0117] In this embodiment, the division module 703 includes: a second query unit 7031, which is used to query the contract record according to the identification code corresponding to the logistics network in the contract request, and analyze the contract record to obtain the contract result, and the contract result includes a successful contract and a failed contract; a first construction unit 7032, which is used to construct two blank sets, respectively as the first network set and the second network set; a division unit 7033, which is used to put the logistics network into the first network set when the contract result corresponding to the logistics network is a failed contract, and put the logistics network into the second network set when the contract result corresponding to the logistics network is a successful contract.

[0118] In this embodiment, the update module 704 includes: a third query unit 7041, which is used to query the contract record for the logistics outlets in the first outlet set according to the identification code corresponding to the logistics outlets; an analysis unit 7042, which is used to analyze the contract record to obtain the reason for the failure of the contract at the logistics outlet, and update the contract request based on the reason for the failure; an update unit 7043, which is used to remove the corresponding logistics outlet from the first outlet set and put it into the second outlet set when the contract result of the logistics outlet is a successful contract.

[0119] In this embodiment, the prediction module 705 includes: a second construction unit 7051, which is used to construct a recharge amount prediction model based on a BP neural network; a second acquisition unit 7052, which is used to obtain the historical recharge information of the logistics outlets in the second outlet set, and the historical recharge information includes the historical recharge amount and the corresponding recharge time; a prediction unit 7053, which is used to filter out the prediction basic information related to the month to be predicted from the historical recharge information, and input the prediction basic information into the recharge amount prediction model to obtain the monthly pre-charge amount of the month to be predicted, and feed back the monthly pre-charge amount to the logistics outlets.

[0120] In this embodiment, when it is determined that the contract status of a logistics outlet is not signed, the basic information of the logistics outlet is obtained, the basic information of the logistics outlet is verified, and a contract request is generated based on the verified basic information. The logistics outlets are divided into a set of outlets with successful and failed contracts based on the contract results, thereby realizing dynamic management and tracking of the outlet status, and repeatedly analyzing and optimizing the outlets that failed to sign the contract until the contract is successfully signed, thereby enhancing the flexibility and adaptability of the contract process. In addition, the BP neural network prediction model is used to provide the outlets with a monthly precharge amount, which can provide more accurate prediction results based on historical data and current trends, and help the outlets to carry out more scientific financial planning and management.

[0121] above Figure 7 The branch account recharge management device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The branch account recharge management device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0122] Figure 8 800 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 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 may be short-term storage or permanent storage. The program stored in the storage medium 830 may include one or more modules (not shown), and each module may include a series of instruction operations in the 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 on the device 800.

[0123] The 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 860, and / or one or more operating systems 831, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc.

[0124] An embodiment of 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 branch account recharge management method.

[0125] 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.

[0126] 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 all 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 a number of instructions to enable a computer device (which can be a personal computer, a server, or a 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 codes.

[0127] 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 managing recharge of a branch account, characterized in that: The branch account recharge management method includes: Determine whether the contract status of the logistics outlet is unsigned, and if so, obtain basic information of the logistics outlet; Verify the basic information of the logistics outlets, and generate a contract signing request based on the verified basic information; Acquire a contract result corresponding to the contract request according to the contract request, put the logistics outlets with a contract failure result into a first outlet set, and put the logistics outlets with a contract success result into a second outlet set; For the logistics outlets in the first set of outlets, the reasons for the failure of the contract signing of the logistics outlets are obtained, and the contract signing request is updated based on the reasons for the failure of the contract signing, and when the contract signing result of the logistics outlet is a successful contract signing, the logistics outlet is moved from the first set of outlets to the second set of outlets; For the logistics outlets in the second outlet set, the historical recharge information of the logistics outlets is obtained, and based on the historical recharge information, the recharge amount prediction model based on the BP neural network is used to predict the monthly pre-charge amount for the predicted month, and the monthly pre-charge amount is fed back to the logistics outlets.

2. The method for managing the recharge of a branch account according to claim 1, characterized in that: The determining whether the contract status of the logistics outlet is unsigned, and if so, obtaining basic information of the logistics outlet, including: Obtain the identification code of the logistics network point, and query the contract status value of the logistics network point using a SQL statement based on the identification code; Compare the contracted status value with a preset uncontracted status value, and if the two are consistent, determine that the contracted status of the logistics network point is uncontracted; If the contract status of the logistics network point is not signed, the basic information of the logistics network point is obtained.

3. The method for managing the recharge of a branch account according to claim 1, characterized in that: The verifying the basic information of the logistics outlets and generating a contract signing request according to the verified basic information includes: Parsing the basic information of the logistics outlet into multiple fields, and matching the multiple fields with a preset field list, and if the match is successful, determining that the basic information verification has passed; Calling a preset contract signing request template, and filling the verified basic information into the default parameters of the contract signing request template; Generate a signing request based on the filled signing request template.

4. The method for managing the recharge of a branch account according to claim 1, characterized in that: The acquiring a contract result corresponding to the contract request according to the contract request, placing logistics outlets with contract failure results into a first outlet set, and placing logistics outlets with contract success results into a second outlet set, includes: The contract record is obtained according to the identification code corresponding to the logistics outlet in the contract request, and the contract record is analyzed to obtain the contract result, which includes the contract success and the contract failure; Construct two blank sets, which are used as the first network point set and the second network point set respectively; If the contract signing result corresponding to the logistics outlet is a contract signing failure, the logistics outlet will be placed in the first outlet set; if the contract signing result corresponding to the logistics outlet is a contract signing success, the logistics outlet will be placed in the second outlet set.

5. The method for managing the recharge of a branch account according to claim 1, characterized in that: The method of obtaining the reason for the failure of the contract signing of the logistics network in the first network set, and updating the contract signing request based on the reason for the failure of the contract signing, and moving the logistics network from the first network set to the second network set when the contract signing result of the logistics network is a successful contract signing, includes: For the logistics outlets in the first outlet set, query and obtain the contract record according to the identification code corresponding to the logistics outlets; Analyze the contract signing record to obtain the reason why the contract signing failed at the logistics outlet, and update the contract signing request based on the reason why the contract signing failed; When the contract signing result of the logistics network point is successful, the corresponding logistics network point is removed from the first network point set and placed in the second network point set.

6. The method for managing the recharge of a branch account according to claim 1, characterized in that: The method of acquiring historical recharge information of the logistics outlets in the second set of outlets, and predicting the monthly pre-charge amount of the predicted month by using a recharge amount prediction model based on a BP neural network according to the historical recharge information, and feeding back the monthly pre-charge amount to the logistics outlets includes: Construct a recharge amount prediction model based on BP neural network; For a logistics network point in the second network point set, obtaining historical recharge information of the logistics network point, the historical recharge information including a historical recharge amount and a corresponding recharge time; The prediction basic information related to the month to be predicted is filtered out from the historical recharge information, and the prediction basic information is input into the recharge amount prediction model to obtain the monthly pre-charge amount of the month to be predicted, and the monthly pre-charge amount is fed back to the logistics outlets. The prediction basic information at least includes the recharge amount and the corresponding recharge time of the historical months adjacent to the predicted month.

7. The method for managing the recharge of a branch account according to claim 1, characterized in that: The recharge amount prediction model based on the BP neural network is constructed, including: Collect the historical recharge amounts and corresponding recharge times of different logistics outlets as samples; Performing data enhancement on the samples to obtain an enhanced sample data set, and dividing the enhanced sample data set into a training set and a test set; The pre-trained BP neural network is trained using the training set, and the trained BP neural network is tuned using the test set to obtain a recharge amount prediction model.

8. A network account recharge management device, characterized in that: include: A judgment module is used to judge whether the contract status of the logistics network point is unsigned, and if so, obtain the basic information of the logistics network point; A generation module, used to verify the basic information of the logistics outlets and generate a contract signing request based on the verified basic information; a division module, configured to obtain a contract result corresponding to the contract request according to the contract request, put the logistics outlets with a contract failure result into a first outlet set, and put the logistics outlets with a contract success result into a second outlet set; An updating module, configured to obtain the reason why the contract signing of the logistics outlets in the first set of outlets fails, and update the contract signing request based on the reason why the contract signing fails, and when the contract signing result of the logistics outlet is a successful contract signing, move the logistics outlet from the first set of outlets to the second set of outlets; The prediction module is used to obtain the historical recharge information of the logistics outlets in the second outlet set, and use the recharge amount prediction model based on the BP neural network to predict the monthly pre-charge amount of the predicted month according to the historical recharge information, and feed back the monthly pre-charge amount to the logistics outlets.

9. A network account recharge management device, characterized in that: comprising a memory and at least one processor, wherein the memory has computer-readable instructions stored therein; The at least one processor calls the computer-readable instructions in the memory to execute each step of the branch account recharge management method as described in any one of claims 1-7.

10. A computer-readable storage medium having computer-readable instructions stored thereon, characterized in that: When the computer-readable instructions are executed by a processor, the steps of the branch account recharge management method as described in any one of claims 1 to 7 are implemented.

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