Order settlement method, device and equipment for wrong logistics packages, and storage medium

Abstract

The invention discloses a logistics wrong set packet order settlement method, device and equipment and a storage medium. The method comprises the steps of preprocessing multi-dimensional sample data to obtain multi-dimensional training data; training the multi-dimensional training data by using a target model learning algorithm to obtain a wrong set packet identification model; predicting real-time order data in the logistics system in real time based on the wrong set packet identification model to determine a target wrong set packet order; determining target settlement data corresponding to the target wrong set packet based on a cost redistribution algorithm and a compensation money compensation algorithm; and the corresponding relation is integrated into a financial settlement module of the logistics system, so that the financial settlement module automatically settles the target settlement data. According to the method and the device, the wrong collection order in the operation process can be found in time, the influence on the subsequent logistics and financial processes is reduced, the cost share and the compensation amount of the wrong collection order can be calculated, the cost management efficiency is improved, the customer satisfaction is enhanced, and the potential legal risk is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of cluster deployment, and specifically relates to an order settlement method, device, equipment and storage medium for logistics staggered packaging. Background Art

[0002] In the logistics industry, the problem of wrong package collection has always been a headache. This problem refers to the fact that in various links of logistics, due to various unforeseen reasons, customers' packages are mistakenly assigned to other orders, causing customers to receive goods that do not match their purchases, or even completely unable to receive their packages on time. For customers, receiving wrong products means that they need to contact the merchant again for returns and exchanges, which not only wastes their time and energy, but also may cause them to miss important opportunities for use. Secondly, if customers cannot receive their packages on time, they may doubt the reliability of the logistics company, which will affect their trust and loyalty to the logistics company. Moreover, this error not only brings great trouble and inconvenience to customers, seriously affecting their shopping experience, but also damages the reputation and customer relations of logistics companies. The current timely discovery mechanism for wrong package collection and the settlement data settlement mechanism are imperfect, which has a profound impact on customers and logistics companies. Summary of the invention

[0003] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a logistics mis-packaging order settlement, device, equipment and storage medium to solve the problems in the prior art that mis-packaging orders cannot be discovered in time and the settlement mechanism for mis-packaging orders is imperfect.

[0004] According to a first aspect of the present application, a method for settling an order for a logistics mismatched package is provided, the method comprising:

[0005] Obtain multi-dimensional sample data in the logistics system;

[0006] Preprocessing the multi-dimensional sample data to obtain multi-dimensional training data;

[0007] The multi-dimensional training data is trained using a target model learning algorithm to obtain a mismatch packet recognition model, wherein the target model learning algorithm is one of a random forest algorithm and a support vector machine algorithm;

[0008] Based on the mismatched package identification model, real-time order data in the logistics system is predicted in real time to determine the target mismatched package order;

[0009] Based on the cost redistribution algorithm and the compensation compensation algorithm, determine the target settlement data corresponding to the target mismatched set package, the target settlement data including the cost share and the compensation share corresponding to the target mismatched set package, wherein the cost share is determined based on the cost redistribution algorithm, and the compensation amount is determined based on the compensation compensation algorithm;

[0010] The target staggered packaging order, the target settlement data and the corresponding relationship between the two are integrated into the financial settlement module of the logistics system, so that the financial settlement module automatically settles the target settlement data of the staggered packaging order based on the corresponding relationship.

[0011] In some embodiments, the dimensional information of the sample data includes order data information, package tracking information, customer complaint records, and historical misassembled package cases in the logistics system. The preprocessing of the multi-dimensional sample data to obtain multi-dimensional training data includes:

[0012] The sample data corresponding to each dimension of the multi-dimensional sample data is cleaned, feature extracted and normalized to obtain training data corresponding to each dimension.

[0013] In some embodiments, the mismatched package identification model predicts the real-time order data in the logistics system in real time to determine the target mismatched package order, including:

[0014] Obtain the current package collection point, the waiting receipt point, and the waiting receipt grid warehouse to which the waiting receipt point belongs for the current order data;

[0015] If the current package collection point is inconsistent with the to-be-signed-for point and the to-be-signed-for grid warehouse, then the current order data is determined to be the target wrong package collection order;

[0016] If the current packaging network point is consistent with any one of the to-be-signed network point and the to-be-signed grid warehouse, it is determined that the current order data is a correct packaging order.

[0017] In some embodiments, after determining the target settlement data corresponding to the target mismatched package based on the cost redistribution algorithm and the compensation compensation algorithm, the method further includes:

[0018] Obtaining a destination code of the target mismatched package order, and extracting a feature code in the destination code, wherein the feature code is a character of a target character code segment in the destination code;

[0019] Get the checksum calculation parameters and expected checksum;

[0020] Determine the calculation check code of the target mismatched package order based on the check code calculation parameters and the A7 encoding rule;

[0021] When the calculated verification code matches the expected verification code, the target wrong packaging order is updated to a correct packaging order.

[0022] In some embodiments, before determining the target settlement data corresponding to the target mismatched set package based on the cost redistribution algorithm and the compensation compensation algorithm, the method further includes:

[0023] Get the current packaging outlet for the current order data;

[0024] Analyze the network point target type of the current package collection network point;

[0025] Based on the target differentiated packaging scheme corresponding to the target type of the outlet, determining whether the current order data is the target differentiated packaging order;

[0026] When the current order data is the target staggered package order, the step of determining the target settlement data corresponding to the target staggered package based on the cost-sufficient allocation algorithm and the compensation algorithm is executed.

[0027] In some embodiments, the network point target type is one of a plurality of network point types in the logistics system, and before determining whether the current order data is the target differential packaging order based on the target differentiated packaging scheme corresponding to the network point target type, the method further includes:

[0028] Acquire a plurality of the network point types in the logistics system;

[0029] Matching a corresponding package collection condition for each of the network point types to establish a corresponding relationship between the network point type and the package collection condition;

[0030] According to the packaging conditions, a differentiated packaging scheme corresponding to each of the network point types is constructed to obtain a differentiated packaging scheme set, wherein the target differentiated packaging scheme is one of the differentiated packaging schemes.

[0031] In some embodiments, the determining whether the current order data is the target differentiated packaging order based on the target differentiated packaging scheme corresponding to the network point target type includes:

[0032] Obtaining the current actual packaging plan for the current order data;

[0033] Determining an expected packaging scheme for the current order data based on the current order data and a target differentiated packaging scheme for the current order data;

[0034] When the actual packaging scheme is inconsistent with the expected packaging scheme, the current order data is determined to be the target wrong packaging order.

[0035] According to another aspect of the present application, a logistics mismatched package order settlement device is also disclosed, the device comprising:

[0036] The sample data acquisition module is used to acquire multi-dimensional sample data in the logistics system;

[0037] A training data acquisition module, used for preprocessing the multi-dimensional sample data to obtain multi-dimensional training data;

[0038] A mismatched packet recognition model training module is used to train the multi-dimensional training data using a target model learning algorithm to obtain a mismatched packet recognition model, wherein the target model learning algorithm is one of a random forest algorithm and a support vector machine algorithm;

[0039] A target mismatched package vertex determination module is used to predict the real-time order data in the logistics system in real time based on the mismatched package recognition model to determine the target mismatched package order;

[0040] A target settlement data determination module is used to determine the target settlement data corresponding to the target mismatch package based on a cost redistribution algorithm and a compensation compensation algorithm, wherein the target settlement data includes a cost share and a compensation share corresponding to the target mismatch package, wherein the cost share is determined based on the cost redistribution algorithm, and the compensation amount is determined based on the compensation compensation algorithm;

[0041] An integration module is used to integrate the target staggered packaging order, the target settlement data and the corresponding relationship between the two into the financial settlement module of the logistics system, so that the financial settlement module automatically settles the target settlement data of the staggered packaging order based on the corresponding relationship.

[0042] According to another aspect of the present application, an electronic device is also disclosed, which includes a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the electronic device executes each step of the order settlement method for logistics staggered packaging as described in any one of the above items.

[0043] According to another aspect of the present application, a computer-readable storage medium is also disclosed, on which instructions are stored, characterized in that when the instructions are executed by a processor, each step of the order settlement method for logistics staggered packaging as described in any of the above items is implemented.

[0044] The present application includes but is not limited to the following beneficial effects: (1) The present application can predict real-time order data, detect misplaced orders in a timely manner, and reduce the impact on subsequent logistics and financial processes; (2) The present application can calculate the cost share of misplaced orders through a cost redistribution algorithm, optimize resource allocation, and improve the efficiency of cost management. The compensation amount can be calculated through a compensation algorithm to achieve reasonable compensation for target misplaced orders, enhance customer satisfaction, and reduce potential legal risks; (3) The present application can integrate the correspondence between target misplaced orders and target settlement data into the financial settlement module to achieve automated settlement, reduce manual intervention, and improve work efficiency; (4) The present application can pre-process sample data The accuracy and reliability of the training data used to train the wrong package recognition model are improved, and a better basis is provided for the accuracy of the subsequent target wrong package recognition; (5) In the present application, when the current package collection point is inconsistent with the waiting receipt point and the waiting receipt grid warehouse, the current order data is considered to be the target wrong package order. Through double-layer screening, the misscreening rate of the target wrong package order is reduced; (6) The verification code comparison is introduced in the present application to improve the accuracy of the settlement data of the target wrong package order; (7) In the present application, based on the outlet type of the current order data, a differentiated package collection scheme matching the type can be selected to make wrong package judgment, which improves the accuracy of wrong package judgment, thereby improving customer satisfaction and operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0046] Figure 1 This is a flow chart of the order settlement method for logistics mismatched package in the embodiment of the present application;

[0047] Figure 2 It is another flow chart of the order settlement method of the logistics mismatched package in the embodiment of the present application;

[0048] Figure 3 It is another flow chart of the order settlement method of the logistics mismatched package in the embodiment of the present application;

[0049] Figure 4 It is another flow chart of the order settlement method of the logistics mismatched package in the embodiment of the present application;

[0050] Figure 5 It is another flow chart of the order settlement method of the logistics mismatched package in the embodiment of the present application;

[0051] Figure 6 It is another flow chart of the order settlement method of the logistics mismatched package in the embodiment of the present application;

[0052] Figure 7 It is a structural block diagram of an order settlement device for logistics mismatched package collection according to an embodiment of the present application;

[0053] Figure 8 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The embodiment of the present invention provides a method, device, equipment and storage medium for order settlement of logistics mismatched packages, wherein the method includes: obtaining multi-dimensional sample data in the logistics system; preprocessing the multi-dimensional sample data to obtain multi-dimensional training data; training the multi-dimensional training data using a target model learning algorithm to obtain a mismatched package recognition model, wherein the target model learning algorithm is one of a random forest algorithm and a support vector machine algorithm; based on the mismatched package recognition model, real-time order data in the logistics system is predicted in real time to determine a target mismatched package order; based on a cost redistribution algorithm and a compensation compensation algorithm, target settlement data corresponding to the target mismatched package is determined, the target settlement data includes a cost share and a compensation share corresponding to the target mismatched package, wherein the cost share is determined based on the cost redistribution algorithm, and the compensation amount is determined based on the compensation compensation algorithm; integrating the target mismatched package order, the target settlement data and the corresponding relationship between the two into the financial settlement module of the logistics system, so that the financial settlement module automatically settles the target settlement data of the mismatched package order based on the corresponding relationship. This application plan can predict real-time order data, detect misplaced packaging orders in a timely manner, and reduce the impact on subsequent logistics and financial processes; further, through the cost reallocation algorithm, the cost share of the misplaced packaging orders can be calculated, resource allocation can be optimized, and the efficiency of cost management can be improved; the compensation amount can be calculated through the compensation algorithm to achieve reasonable compensation for the target misplaced packaging orders, enhance customer satisfaction, and reduce potential legal risks; further, the correspondence between the target misplaced packaging orders and the target settlement data can be integrated into the financial settlement module to achieve automated settlement, reduce manual intervention, and improve work efficiency.

[0055] 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.

[0056] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 An embodiment of the order settlement method for logistics mismatched package in the embodiment of the present invention includes:

[0057] S100. Acquire multi-dimensional sample data in the logistics system.

[0058] In one example, the dimensional information of the sample data may include, but is not limited to, order data information, package tracking information, customer complaint records, and historical mis-assembly cases in the logistics system. It is understandable that the order data information may be all order data within a target time period in the logistics system, the package tracking information may be the transit route information of each order data, the customer complaint record may be the complaint record stored in the background, and the historical mis-assembly case may be the order information corresponding to the historical mis-assembly stored in the background.

[0059] S102: Preprocess the multi-dimensional sample data to obtain multi-dimensional training data.

[0060] In one example, preprocessing the multidimensional sample data to obtain the multidimensional training data can be to perform data cleaning, feature extraction and data normalization on the sample data corresponding to each dimension of the multidimensional sample data to obtain the training data corresponding to each dimension, so that after completing the above preprocessing of the sample data of all dimensions, the training data corresponding to each dimension and the multidimensional training data can be obtained. It can be understood that by preprocessing the sample data, the accuracy and reliability of the training data used to train the mismatch package recognition model are improved, providing a better basis for the accuracy of the subsequent recognition of the target mismatch package.

[0061] S104: Use the target model learning algorithm to train the multi-dimensional training data to obtain a wrong set packet recognition model.

[0062] In one example, the target model learning algorithm may be a random forest algorithm. The random forest algorithm is an ensemble learning algorithm based on decision trees, which performs classification or regression by constructing multiple decision trees and combining their outputs. The random forest uses the bootstrap resampling technique to repeatedly randomly extract samples with replacement from the original training sample set to generate a new training sample set, and then generates a decision tree based on each new sample set to form a random forest. The prediction results of multiple decision trees can be averaged (regression) or voted (classification), effectively reducing the risk of a single decision tree overfitting the training data and improving the accuracy and stability of the wrong set package recognition model. In one example, when using the random forest algorithm to build a mis-aggregate package identification model, in addition to the above dimensions of sample data, features of more dimensions can be added to enhance the model's recognition capabilities. For example, package volume and weight deviation can be added: analyze the difference between the actual volume and weight of the package and the system record value. Abnormal deviation may indicate mis-aggregation. Route deviation analysis can also be added: compare the difference between the actual transportation route of the package and the planned route. Abnormal deviation may mean delivery error. Customer behavior patterns can also be added: analyze the customer's historical complaint frequency, purchasing habits, etc. to identify potential sensitive customers whose complaints may be more likely to point to real problems. Time series analysis can also be added: apply time series analysis techniques to identify abnormal delays in package processing time, which may be caused by mis-aggregate packages.

[0063] In another example, the target model learning algorithm may also be a support vector machine algorithm, which has good generalization ability and can maintain high prediction accuracy when there is less multi-dimensional training data. The prediction accuracy of subsequent order data will not be affected by less multi-dimensional training data.

[0064] S106. Based on the mismatched package recognition model, real-time order data in the logistics system is predicted in real time to determine the target mismatched package order.

[0065] Specifically, the order data can be input into the mismatched package recognition model in real time, and the order data input in real time can be predicted based on the mismatched package recognition model, so as to predict the target mismatched package order. Figure 2 The flowchart is based on the mismatched package recognition model to determine the target mismatched package order. When the current order data is input into the mismatched package recognition model, the mismatched package recognition model is executed. Figure 2 The output results after the following steps are shown:

[0066] S200, obtaining the current package collection point, the to-be-signed point, and the to-be-signed grid warehouse to which the to-be-signed point belongs for the current order data.

[0067] Among them, the current package collection point is the current logistics node responsible for aggregating, classifying and packing multiple packages, and the waiting-for-signature point is the last logistics node before the last mile delivery of the order package, usually the distribution station or express delivery point closest to the recipient; the waiting-for-signature grid warehouse to which the waiting-for-signature point belongs is a regional warehouse responsible for managing and supporting the operation of multiple waiting-for-signature points, usually covering a larger geographical area, and acting as an intermediate node to ensure that the order package can be smoothly transferred from the package collection point to each waiting-for-signature point. It is understandable that the waiting-for-signature point and the waiting-for-signature grid warehouse to which the waiting-for-signature point belongs can be determined based on the cross-regional routes of the order's shipping address and receiving address.

[0068] S202: If the current package collection point is inconsistent with the to-be-signed-for point and the to-be-signed-for grid warehouse, the current order data is determined to be the target wrong package collection order.

[0069] Specifically, if the current package collection point is inconsistent with the waiting receipt point and the waiting receipt grid warehouse, it means that the order package corresponding to the current order data has been incorrectly packaged, and the order package corresponding to the current order data is considered to be the target wrong package collection order.

[0070] S204: If the current package collection point is consistent with the to-be-signed-for point and any one of the to-be-signed-for grid warehouses, it is determined that the current order data is a correct package collection order.

[0071] Specifically, if the current package collection point is the same as any one of the waiting receipt point and the waiting receipt grid warehouse, it means that the order package corresponding to the current order data is running according to the normal operation route and has not been incorrectly sub-packaged. Then the order package corresponding to the current order data is considered to be the target wrong package collection order.

[0072] In this embodiment, when the current package collection point is inconsistent with the waiting receipt point and the waiting receipt grid warehouse, the current order data is considered to be the target wrong package collection order. Through double-layer screening, the screening rate of the target wrong package collection order is reduced;

[0073] S108. Based on the cost reallocation algorithm and the compensation algorithm, determine the target settlement data corresponding to the target misaligned package, the target settlement data including the cost share and the compensation share corresponding to the target misaligned package.

[0074] Among them, the cost share is determined based on the cost redistribution algorithm, and the compensation amount is determined based on the compensation compensation algorithm. Specifically, the cost redistribution algorithm can be pre-constructed, which can be a proportional allocation method, that is, allocating costs according to the specific proportion of each participant, or an activity-based cost method, that is, allocating costs according to the actual resource consumption of each participant. In this example, the proportional allocation method is selected, in which the proportions of each participant are different, and the specific proportion values ​​can be pre-set. When calculating based on the cost redistribution algorithm, it is necessary to consider not only direct costs, but also indirect costs and opportunity costs. Among them, direct costs include actual redistribution costs, return costs, commodity replacement costs, etc. Indirect costs include, for example, the loss of customer satisfaction caused by the wrong assembly of packages, the loss of market value implied by the damage to the brand image, etc. Opportunity costs include considering the resources occupied by processing the wrong assembly of packages, and the value that may be created if used for other businesses. When pre-constructing the cost redistribution algorithm, multi-objective optimization technology is used to balance the relationship between various costs to balance the cost sharing of each participant (company, customer, third-party logistics, etc.).

[0075] It can be understood that in this embodiment, the cost shares of different participants are calculated based on different ratios, and the costs to be shared can be determined based on the participation of different participants in each link. This can effectively balance the cost sharing of each participant, reduce disputes caused by uneven sharing, optimize resource allocation, and improve the efficiency of cost management.

[0076] Furthermore, the compensation algorithm is pre-constructed. When constructing the compensation algorithm, it is not only based on objective standards, but also needs to be combined with subjective factors such as the number of days of delay and the value coefficient of the goods: different compensation coefficients are set according to the number of days of delay and the actual value of the goods. It can also be affected by customer level, for example, VIP customers or high-value customers may enjoy a higher compensation ratio to maintain customer loyalty. Further consideration is given to legal and policy adaptability, such as ensuring that the amount of compensation complies with local laws and regulations to avoid additional legal risks. Further consideration can be given to the personalization of the company's compensation rules, such as combining company-specific compensation policies, such as special compensation rules during holidays and special events. In one example, the compensation algorithm can be a proportional apportionment method, which apportions the compensation according to the proportion of each party's responsibility in the loss. It can be understood that in this embodiment, the compensation amount can be calculated by the compensation algorithm to achieve reasonable compensation for the target mismatched package order, enhance customer satisfaction, and reduce potential legal risks.

[0077] S110, integrating the target mismatched packaging order, the target settlement data and the corresponding relationship between the two into the financial settlement module of the logistics system, so that the financial settlement module automatically settles the target settlement data of the mismatched packaging order based on the corresponding relationship.

[0078] In one example, an API interface can be developed to integrate the target package order, target settlement data, and the corresponding relationship between the two into the financial settlement module of the logistics system. When designing the API interface, first define the API endpoint and request method, determine the data format of the request and response, further create the API processing logic, integrate the data into the financial settlement module, and finally use tools (such as Postman) or write test code for verification, thereby completing the development of the API interface with target requirements.

[0079] Furthermore, the automatic settlement content of the financial settlement module can include automatic bill generation, that is, automatically generating clear and detailed wrong set package order bills based on the processing results, including details of various expenses, and can also include automated compensation processes, that is, automatically triggering compensation payment processes through the system, including transferring money to customer accounts, sending compensation notices, etc. It can also include internal cost adjustment automation: automatically adjusting cost allocation in the company's internal accounting system to ensure the accuracy of financial statements and support financial analysis and decision-making. It can also include monitoring and auditing, that is, establishing a complete monitoring and auditing mechanism to regularly review the accuracy and efficiency of automatic settlement processing, and promptly discover and correct problems.

[0080] Furthermore, Figure 3 This is another flow chart of the order settlement method for logistics mismatched packages. The method shown in this flow chart is applied to the step S108 introduced above, based on the cost redistribution algorithm and the compensation algorithm, and then the target settlement data corresponding to the target mismatched package is determined and executed. Specifically, referring to 3, the steps include:

[0081] S300: Obtain the destination code of the target mismatched package order, and extract the feature code in the destination code.

[0082] The characteristic code is the characters of the target code segment in the destination code. The target code segment can be the first 5 characters of the destination address, or the middle 8 characters of the destination address.

[0083] S302: Obtain verification code calculation parameters and expected verification code.

[0084] Specifically, the expected check code may be set preferentially, and may be a specific check value. The check code calculation parameter may be a pre-set coefficient value.

[0085] S304: Determine the calculation check code of the target error-collection package order based on the check code calculation parameters and the A7 encoding rule.

[0086] Specifically, the A7 encoding rule is a standard for data verification and encoding, which is commonly used in logistics and information systems. It ensures the integrity and accuracy of data through specific character encoding and verification mechanisms. Specifically, the A7 encoding rule includes the following aspects: character set, which is used to specify the range and type of characters used, such as letters, numbers and special symbols. The encoding structure is used to define how data is encoded in a specific format, including the use of segmentation and identifiers. The verification mechanism is used to ensure that the data has not been tampered with or damaged during transmission and storage by calculating the check code. Application scenarios are mostly used in logistics, warehousing and distribution, etc. to ensure the accuracy of order and package information. In this example, based on the check code calculation parameters and the A7 encoding rule, the calculated check code of the target wrong package order is determined. Specifically, the check code calculated based on the A7 encoding rule can be multiplied by the check code calculation parameters as the calculated check code of the target wrong package order.

[0087] S306: When the calculated check code matches the expected check code, the target wrong package order is updated to a correct package order.

[0088] Specifically, when the calculated verification code matches the preset expected verification code, it is considered that the target wrong packaging order is not wrongly packaged. At this time, the target wrong packaging order needs to be updated to a correct packaging order.

[0089] In this embodiment, the verification code comparison is introduced to improve the accuracy of the settlement data of the target mismatched package order.

[0090] Furthermore, Figure 4 This is another flow chart of a method for settling orders for logistics mismatched packages. The method shown in this flow chart is applied to the step S108 introduced above, based on the cost redistribution algorithm and the compensation algorithm, and is executed before determining the target settlement data corresponding to the target mismatched package. Specifically, referring to step 4, the steps include:

[0091] S400, obtaining the current packaging outlet for the current order data.

[0092] S402, analyzing the network point target type of the current package network point.

[0093] Specifically, the types of the package collection outlets may include but are not limited to grid warehouse types, common outlet types, B types classified by product categories (such as electronic products and non-electronic products), etc. When analyzing the outlet target type of the current package collection outlet, the package collection outlet and type correspondence table may be searched to determine.

[0094] S404: Determine whether the current order data is a target mismatch order based on a target differentiated packaging solution corresponding to the target type of the outlet.

[0095] Specifically, when determining the target type of the current packaging outlet, the target differentiated packaging scheme corresponding to the outlet target type can be searched based on the outlet type and the differentiated packaging scheme, thereby determining whether the current order data is a target wrong packaging order based on the target differentiated packaging scheme.

[0096] S406: When the current order data is a target mismatch package order, a step of determining target settlement data corresponding to the target mismatch package based on a cost full allocation algorithm and a compensation algorithm is executed.

[0097] In this embodiment, based on the outlet type of the current order data, a differentiated packaging scheme that matches the type can be selected to perform mis-packaging judgment, thereby improving the accuracy of mis-packaging judgment and thus improving customer satisfaction and operational efficiency.

[0098] Furthermore, Figure 5 Another flow chart of a logistics staggered package order settlement method, the method shown in the flow chart is applied to the above-mentioned step S404, based on the target differentiated package scheme corresponding to the target type of the outlet, before determining whether the current order data is a target staggered package order, specifically, refer to Figure 5 , the process steps include:

[0099] S500. Acquire multiple outlet types in the logistics system.

[0100] S502: Match a corresponding package collection condition for each network point type to establish a corresponding relationship between the network point type and the package collection condition.

[0101] S504: construct a differentiated packaging scheme corresponding to each network point type according to the packaging conditions to obtain a differentiated packaging scheme set.

[0102] The target differentiated packaging scheme is one of the differentiated packaging schemes. The packaging conditions may include but are not limited to the rate conditions corresponding to the order data in the logistics system for each type of outlet, the weight requirement conditions, and the distribution method of the order data at each type of outlet (manual line or automatic line, etc.). In one example, when the distribution method of the order data is manual line, the manually distributed order packages are determined based on the differentiated packaging scheme. When the distribution method of the order data is automatic line, all order packages corresponding to the outlet are determined based on the differentiated packaging scheme.

[0103] Figure 6 This is another flow chart of a logistics staggered package order settlement method. The method shown in this flow chart is the step S404 introduced above, based on the target differentiated package scheme corresponding to the target type of the outlet, determining whether the current order data is a target staggered package order. Specifically, refer to step 6, the steps include:

[0104] S600: Obtain the current actual packaging solution for the current order data.

[0105] Specifically, each type of package collection point corresponds to a package collection solution.

[0106] S602: Determine an expected packaging scheme for the current order data based on the current order data and the target differentiated packaging scheme for the current order data.

[0107] Specifically, the expected packaging plan is a packaging plan predicted based on the current order data and the target differentiated packaging plan corresponding to the current order data.

[0108] S604: When the actual packaging plan is inconsistent with the expected packaging plan, determine the current order data as the target wrong packaging order.

[0109] Specifically, when the actual packaging plan is inconsistent with the predicted expected packaging plan, it means that the order package corresponding to the current order data is incorrectly packaged, and the order package corresponding to the current order data is considered to be the target incorrect packaging order.

[0110] The above describes the order settlement method of the logistics staggered package in the embodiment of the present invention. The following describes the order settlement device of the logistics staggered package in the embodiment of the present invention. Figure 7 In one embodiment of the present invention, an order settlement device for logistics staggered package collection includes:

[0111] The sample data acquisition module is used to acquire multi-dimensional sample data in the logistics system;

[0112] A training data acquisition module is used to preprocess multi-dimensional sample data to obtain multi-dimensional training data;

[0113] A mismatched packet recognition model training module is used to train multi-dimensional training data using a target model learning algorithm to obtain a mismatched packet recognition model, wherein the target model learning algorithm is one of a random forest algorithm and a support vector machine algorithm;

[0114] The target mismatched package vertex determination module is used to predict the real-time order data in the logistics system in real time based on the mismatched package identification model to determine the target mismatched package order;

[0115] A target settlement data determination module is used to determine the target settlement data corresponding to the target mismatch package based on the cost redistribution algorithm and the compensation compensation algorithm, wherein the target settlement data includes the cost share and the compensation share corresponding to the target mismatch package, wherein the cost share is determined based on the cost redistribution algorithm, and the compensation amount is determined based on the compensation compensation algorithm;

[0116] The integration module is used to integrate the target mismatched packaging order, the target settlement data and the corresponding relationship between the two into the financial settlement module of the logistics system, so that the financial settlement module can automatically settle the target settlement data of the mismatched packaging order based on the corresponding relationship.

[0117] The application introduction of the relevant modules of the device in this example can refer to the relevant introduction of the principle of the above method, which will not be repeated here.

[0118] above Figure 7 The order settlement device for logistics staggered packaging 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.

[0119] Figure 8 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 short-term storage or permanent storage. The program stored in the storage medium 830 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the electronic device 800. Furthermore, the processor 810 can 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.

[0120] 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 Figure 8 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.

[0121] 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 a method for settling an order for logistics mismatched packages.

[0122] 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.

[0123] 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, in essence, 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, which is stored in a storage medium and includes several instructions for 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 methods of 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, etc., various media that can store program codes.

[0124] 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 settling orders for logistics mismatched packages, characterized in that: The method comprises: Obtain multi-dimensional sample data in the logistics system; Preprocessing the multi-dimensional sample data to obtain multi-dimensional training data; The multi-dimensional training data is trained using a target model learning algorithm to obtain a mismatch packet recognition model, wherein the target model learning algorithm is one of a random forest algorithm and a support vector machine algorithm; Based on the mismatched package identification model, real-time order data in the logistics system is predicted in real time to determine the target mismatched package order; Based on the cost redistribution algorithm and the compensation compensation algorithm, determine the target settlement data corresponding to the target mismatched set package, the target settlement data including the cost share and the compensation share corresponding to the target mismatched set package, wherein the cost share is determined based on the cost redistribution algorithm, and the compensation amount is determined based on the compensation compensation algorithm; The target staggered packaging order, the target settlement data and the corresponding relationship between the two are integrated into the financial settlement module of the logistics system, so that the financial settlement module automatically settles the target settlement data of the staggered packaging order based on the corresponding relationship.

2. The method for settling orders for logistics mismatched packages according to claim 1, characterized in that: The dimensional information of the sample data includes order data information, package tracking information, customer complaint records and historical mis-package cases in the logistics system. The multi-dimensional sample data is pre-processed to obtain multi-dimensional training data including: The sample data corresponding to each dimension of the multi-dimensional sample data is cleaned, feature extracted and normalized to obtain training data corresponding to each dimension.

3. The method for settling orders for logistics staggered packages according to claim 1 is characterized in that: The mismatched package identification model predicts the real-time order data in the logistics system in real time to determine the target mismatched package order, including: Obtain the current package collection point, the waiting receipt point, and the waiting receipt grid warehouse to which the waiting receipt point belongs for the current order data; If the current package collection point is inconsistent with the to-be-signed-for point and the to-be-signed-for grid warehouse, then the current order data is determined to be the target wrong package collection order; If the current packaging network point is consistent with any one of the to-be-signed network point and the to-be-signed grid warehouse, it is determined that the current order data is a correct packaging order.

4. The method for settling orders for logistics mismatched packages according to claim 1, characterized in that: After determining the target settlement data corresponding to the target mismatched package based on the cost redistribution algorithm and the compensation compensation algorithm, the method further includes: Obtaining a destination code of the target mismatched package order, and extracting a feature code in the destination code, wherein the feature code is a character of a target character code segment in the destination code; Get the checksum calculation parameters and expected checksum; Determine the calculation check code of the target mismatched package order based on the check code calculation parameters and the A7 encoding rule; When the calculated verification code matches the expected verification code, the target wrong packaging order is updated to a correct packaging order.

5. The order settlement method for logistics mismatched packaging according to claim 1 is characterized in that Before determining the target settlement data corresponding to the target mismatched set package based on the cost redistribution algorithm and the compensation compensation algorithm, the method further includes: Get the current packaging outlet for the current order data; Analyze the network point target type of the current package collection network point; Based on the target differentiated packaging scheme corresponding to the target type of the outlet, determining whether the current order data is the target differentiated packaging order; When the current order data is the target staggered package order, the step of determining the target settlement data corresponding to the target staggered package based on the cost-sufficient allocation algorithm and the compensation algorithm is executed.

6. The method for settling orders for logistics mismatched packages according to claim 5, characterized in that: The network point target type is one of a plurality of network point types in the logistics system. Before determining whether the current order data is the target differential packaging order based on the target differentiated packaging scheme corresponding to the network point target type, the method further includes: Acquire a plurality of the network point types in the logistics system; Matching a corresponding package collection condition for each of the network point types to establish a corresponding relationship between the network point type and the package collection condition; According to the packaging conditions, a differentiated packaging scheme corresponding to each of the network point types is constructed to obtain a differentiated packaging scheme set, wherein the target differentiated packaging scheme is one of the differentiated packaging schemes.

7. The method for settling orders for logistics mismatched packages according to claim 6, characterized in that: The determining whether the current order data is the target differentiated packaging order based on the target differentiated packaging scheme corresponding to the target type of the network point includes: Obtaining the current actual packaging plan for the current order data; Determining an expected packaging scheme for the current order data based on the current order data and a target differentiated packaging scheme for the current order data; When the actual packaging scheme is inconsistent with the expected packaging scheme, the current order data is determined to be the target wrong packaging order.

8. An order settlement device for logistics mismatched packaging, characterized in that: The device comprises: The sample data acquisition module is used to acquire multi-dimensional sample data in the logistics system; A training data acquisition module, used for preprocessing the multi-dimensional sample data to obtain multi-dimensional training data; A mismatched packet recognition model training module is used to train the multi-dimensional training data using a target model learning algorithm to obtain a mismatched packet recognition model, wherein the target model learning algorithm is one of a random forest algorithm and a support vector machine algorithm; A target mismatched package vertex determination module is used to predict the real-time order data in the logistics system in real time based on the mismatched package recognition model to determine the target mismatched package order; A target settlement data determination module is used to determine the target settlement data corresponding to the target mismatch package based on a cost redistribution algorithm and a compensation compensation algorithm, wherein the target settlement data includes a cost share and a compensation share corresponding to the target mismatch package, wherein the cost share is determined based on the cost redistribution algorithm, and the compensation amount is determined based on the compensation compensation algorithm; An integration module is used to integrate the target staggered packaging order, the target settlement data and the corresponding relationship between the two into the financial settlement module of the logistics system, so that the financial settlement module automatically settles the target settlement data of the staggered packaging order based on the corresponding relationship.

9. An electronic device, comprising a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the electronic device executes each step of the order settlement method for logistics staggered packages as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the order settlement method for logistics staggered packaging as described in any one of claims 1-7 are implemented.

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