Logistics order control method and device, equipment and storage medium

Abstract

The invention discloses a logistics order control method, apparatus and device, and a storage medium. The method comprises the steps of obtaining a target logistics order and a current logistics track corresponding to the target logistics order; obtaining a target node of the target logistics order under the target business demand and a screening condition of the target node; based on the screening condition, screening out a target node of the target logistics order from the current logistics track and displaying the target node to the user; obtaining a logistics analysis model; analyzing the logistics behavior of the target logistics order based on the logistics analysis model and the target node; determining a logistics control mechanism of the target logistics order based on the logistics behavior; and controlling the target order based on the logistics control mechanism. According to the invention, the logistics behavior control of the target logistics order can be realized in combination with the current logistics track and the current business demand, the logistics strategy and operation can be adjusted in real time, the market change and the customer demand can be quickly responded, and the flexibility and adaptability of logistics transportation are improved.

Description

Technical Field

[0001] The present invention belongs to the field of logistics and transportation technology, and specifically relates to a logistics order control method, device, equipment and storage medium. Background Art

[0002] With the rapid development of e-commerce, the accurate and timely delivery of logistics information has become one of the key factors that determine user experience. However, the large amount of data generated in the logistics process has brought challenges to the effective management and display of information. Traditional processing methods are often difficult to cope with complex business logic and real-time requirements, and are prone to information redundancy or omission of important nodes. Effective logistics order control methods can not only improve the control flexibility and adaptability of logistics transportation orders, but also improve customer satisfaction. Therefore, it is particularly important to research and develop efficient logistics order control methods. 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 order control method, device, equipment and storage medium to solve the problems in the prior art that logistics transportation order control is single, flexible and low matching with business needs.

[0004] According to one aspect of the present application, a logistics order control method is disclosed, the method comprising:

[0005] Obtaining a target logistics order and a current logistics track corresponding to the target logistics order;

[0006] Obtaining a target node of the target logistics order under a target business requirement and a screening condition of the target node;

[0007] Based on the screening condition, the target node of the target logistics order is screened out from the current logistics track and displayed to the user;

[0008] Acquire a logistics analysis model matching the target node;

[0009] Based on the logistics analysis model and the target node, analyzing the logistics behavior of the target logistics order;

[0010] Based on the logistics behavior, determining a logistics control mechanism for the target order;

[0011] The target order is controlled based on the logistics control mechanism.

[0012] In some implementations, the obtaining of the target node of the target logistics order under the target business requirement and the screening condition of the target node includes:

[0013] Obtain the correspondence between business requirements, node information, and screening conditions;

[0014] Based on the corresponding relationship, the target node of the target logistics order under the target business demand and the screening conditions of the target node are searched.

[0015] In some implementations, based on the screening condition, screening the target node of the target logistics order from the current logistics track and displaying it to the user includes:

[0016] Based on a dynamic filtering rule engine, the target node of the target logistics order is filtered out from the current logistics track and displayed to the user, wherein the filtering conditions are written into the dynamic filtering rule engine and the filtering conditions are editable in the dynamic filtering rule engine.

[0017] In some embodiments, the target node includes a target scan type, a target time period, and target remark information, and the method further includes:

[0018] Based on the target scan type and the target remark information, determine the status information of the target logistics order, wherein the status information includes the signing status or the reverse logistics status;

[0019] When the status information is a proxy signing status, remove the secondary delivery mark;

[0020] When the status information is a reverse logistics status, the reverse transportation time of the target logistics order is marked.

[0021] In some embodiments, before obtaining the logistics analysis model, the method further includes establishing the logistics analysis model, including:

[0022] Obtain multiple sample logistics orders and sample logistics trajectory data corresponding to each of the sample logistics orders;

[0023] Preprocessing each of the sample logistics trajectory data to obtain a plurality of preprocessed trajectory data;

[0024] Based on the model requirement, extracting a plurality of feature trajectory data matching the model requirement from the plurality of pre-processed trajectory data, wherein the feature trajectory data is used to match the target node;

[0025] Based on the plurality of characteristic trajectory data, the logistics analysis model is determined.

[0026] In some embodiments, the preprocessing of each sample logistics trajectory data to obtain a plurality of preprocessed trajectory data comprises:

[0027] Removing invalid data from the sample logistics trajectory data based on a missing value processing algorithm;

[0028] Identify and remove abnormal characters or erroneous records in data based on regular expression matching and denoising algorithms;

[0029] Time data in different formats are unified into a specific standard format based on the time conversion function.

[0030] In some embodiments, the logistics behavior includes activity periodicity behavior, transport trend, and transport abnormality behavior, and analyzing the logistics behavior of the target logistics order based on the logistics analysis model and the target node includes:

[0031] Based on the logistics analysis model, analyzing whether the target logistics order meets the activity periodicity behavior;

[0032] Based on the target node, the transfer trend of the target logistics order and the abnormal transfer behavior of the target logistics order are analyzed.

[0033] According to another aspect of the present application, a logistics order control device is also disclosed, the device comprising:

[0034] A first acquisition module is used to acquire a target logistics order and a current logistics track corresponding to the target logistics order;

[0035] A second acquisition module is used to acquire a target node of the target logistics order under a target business requirement and a screening condition of the target node;

[0036] A screening module, used for screening the target node of the target logistics order from the current logistics track based on the screening condition and displaying it to the user;

[0037] The third acquisition module is used to acquire a logistics analysis model;

[0038] A logistics behavior analysis module, used to analyze the logistics behavior of the target logistics order based on the logistics analysis model and the target node;

[0039] A logistics control mechanism determination module, used to determine the logistics control mechanism of the target order based on the logistics behavior;

[0040] A control module is used to control the target order based on the logistics control mechanism.

[0041] According to another aspect of the present application, the present application also discloses an electronic device, 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 the various steps of the logistics order control method as described above.

[0042] According to another aspect of the present application, the present application also discloses a computer-readable storage medium, on which instructions are stored, characterized in that when the instructions are executed by a processor, the various steps of the logistics order control method as described above are implemented.

[0043] The present invention includes but is not limited to the following beneficial effects: (1) This application can combine the current logistics trajectory and current business needs to realize the logistics behavior control of the target logistics order, can adjust the logistics strategy and operation in real time, quickly respond to market changes and customer needs, and improve the flexibility and adaptability of logistics transportation; (2) By setting the target node and its screening conditions, this application can more accurately locate the key nodes of the order in the logistics process, help users quickly obtain relevant information, and improve decision-making efficiency; (3) This application can deeply analyze the logistics behavior of the target order, identify potential problems and bottlenecks, and then optimize the logistics process and improve overall efficiency. According to the results of the logistics behavior analysis, it can formulate a targeted logistics control mechanism to meet different business needs and improve service quality and customer satisfaction; (4) By obtaining the correspondence between business needs, node information and screening conditions, it can ensure that the target node of the target logistics order is highly consistent with the actual business needs, thereby And improve the pertinence and effectiveness of logistics management; (5) The editability of the dynamic filtering rule engine enables users to customize filtering conditions according to their own needs, which improves user participation and satisfaction and optimizes the overall user experience. This flexibility can adapt to diverse business needs and improve the application capabilities of logistics control management in different environments; (6) This application can determine the status information of the target logistics order based on the target scanning type and target note information, and remove the secondary delivery mark when the status information is the proxy signing status, which can reduce unnecessary delivery and information interference, optimize the delivery process, and improve logistics efficiency; and, when the status information is reverse logistics, marking the reverse logistics time can help logistics managers clearly understand the progress of reverse logistics and facilitate subsequent processing and tracking; (7) This application can predict the transfer trend and abnormal behavior of the target logistics, facilitate the early planning of the logistics scheduling mechanism, and reduce the risks and losses in the logistics process. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] 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.

[0045] Figure 1 It is a flow chart of the logistics order control method of the embodiment of the present application;

[0046] Figure 2 It is another flow chart of the logistics order control method of the embodiment of the present application;

[0047] Figure 3 It is another flow chart of the logistics order control method of the embodiment of the present application;

[0048] Figure 4 is a structural block diagram of a logistics order control device according to an embodiment of the present application;

[0049] Figure 5 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The embodiment of the present invention provides a logistics order control method, including obtaining a target logistics order and a current logistics track corresponding to the target logistics order; obtaining a target node of the target logistics order under a target business demand and a screening condition of the target node; based on the screening condition, screening the target node of the target logistics order from the current logistics track and displaying it to a user; obtaining a logistics analysis model; based on the logistics analysis model and the target node, analyzing the logistics behavior of the target logistics order; based on the logistics behavior, determining the logistics control mechanism of the target logistics order; and controlling the target order based on the logistics control mechanism. The present application can realize the logistics behavior control of the target logistics order in combination with the current logistics track and the current business demand, can adjust the logistics strategy and operation in real time, quickly respond to market changes and customer needs, and improve the flexibility and adaptability of logistics transportation.

[0051] 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.

[0052] For ease of understanding, the specific process of the embodiment of the present invention is described below. Specifically, Figure 1 This is a flow chart of the logistics order control method of this application, and the steps include:

[0053] S100: Obtain a target logistics order and a current logistics track corresponding to the target logistics order.

[0054] In one example, logistics orders that require attention can be screened out as target logistics orders based on specific conditions (such as customer demand, order status, time period, etc.). These conditions can be set by user input or automatically by the system. The target logistics order can also be confirmed based on a unique identifier (such as an order number) to ensure the accuracy of subsequent operations. Furthermore, after obtaining the target logistics order, it can be connected to a logistics management system, a database, or other information source to extract order data information related to the target logistics order. Among them, these order data information may include but are not limited to the place of shipment and destination, mode of transportation (such as land transportation, sea transportation, air transportation, etc.) order status (such as pending shipment, in transit, completed, etc.).

[0055] Furthermore, the current logistics trajectory data of the target logistics order can be obtained from the logistics tracking system or real-time monitoring platform, where the trajectory data may include but is not limited to the current location (GPS coordinates or geographic location), various nodes in the transportation process (such as transfer stations, distribution centers, etc.) and timestamps (arrival and departure times of each node), etc.

[0056] S102: Obtain a target node for a target logistics order under a target business requirement and a screening condition for the target node.

[0057] Among them, the target business requirement can be to only display meaningful information to the user. Furthermore, in one example, obtaining the target node of the target logistics order under the target business requirement and the filtering conditions of the target node can be to first obtain the correspondence between the business requirement, node information and the filtering conditions, and then further search for the target node of the target logistics order under the target business requirement and the filtering conditions of the target node based on the correspondence. Exemplarily, taking the target business requirement of only displaying meaningful information to the user as an example, at this time, the target node can include the target scan type, target time period and target remark information. That is, only the target scan type, target time period and target remark information of the target logistics order are displayed to the user.

[0058] Furthermore, the above target business demand is to display meaningful information to users, which is only an exemplary explanation. In other feasible solutions, the target business demand can also be to check the logistics data one by one. Once a piece of data meets any filtering condition, a processing decision is made immediately, such as display, ignore or further analysis, which greatly improves the processing efficiency. Furthermore, the target business demand can also be for specific business needs, such as the display of logistics information related to Douyin. The system can accurately match the order number regular expression and time range. At the same time, the system intelligently identifies and blocks scan types that are no longer operated by internal business, reduces invalid information push, and optimizes user experience. For the trajectory of intercity communication products and postal returns, the system has designed special logic to ensure that these nodes can be displayed normally under specific conditions and enhance information integrity. Special processing of specific scan types (such as 13, 16, 81, etc.) and intelligent analysis of scanned employee IDs ensure the accuracy and security of information.

[0059] S104: Based on the screening conditions, the target node of the target logistics order is screened out from the current logistics track and displayed to the user.

[0060] Specifically, based on the dynamic filtering rule engine, the target node of the target logistics order can be filtered out from the current logistics track and displayed to the user, wherein the dynamic filtering rule engine has filtering conditions written therein, and the filtering conditions are editable in the dynamic filtering rule engine. It is understandable that the filtering conditions are written into the dynamic filtering rule engine, and the filtering conditions are editable in the dynamic filtering rule engine, so that the dynamic filtering rule engine can process and filter data in real time based on the preset filtering conditions, so as to quickly identify and extract the target node in the data stream. Furthermore, after filtering out the target node of the target logistics order, it is displayed to the user. It is understandable that the editability of the dynamic filtering rule engine enables users to customize the filtering conditions according to their own needs, thereby improving the user's sense of participation and satisfaction, optimizing the overall user experience, and this flexibility can adapt to diverse business needs and improve the application capabilities of the logistics control management in different environments.

[0061] S106. Obtain a logistics analysis model that matches the target node.

[0062] Specifically, a logistics analysis model can be pre-established and stored in a model library, and when needed, the logistics analysis model can be directly obtained from the model library. It can be understood that the obtained logistics analysis model matches the target node, and accurate analysis of the target logistics order based on the target node can be achieved.

[0063] S108. Analyze the logistics behavior of the target logistics order based on the logistics analysis model and the target node.

[0064] In one example, logistics behavior may include but is not limited to activity periodic behavior, transfer trend, and transfer abnormal behavior. When the logistics behavior includes these three behaviors, analyzing the logistics behavior of the target logistics order based on the logistics analysis model and the target node may be: based on the logistics analysis model, analyzing whether the target logistics order meets the activity periodic behavior, and based on the target node, analyzing the transfer trend and transfer abnormal behavior of the target logistics order.

[0065] In one example, activity periodic behavior may include but is not limited to order processing cycle, transportation cycle, inventory turnover cycle, etc. At this time, the logistics analysis model may specifically be a periodic behavior logistics analysis model. Therefore, based on the logistics analysis model, analyzing whether the target logistics order satisfies the activity periodic behavior may specifically be based on the activity periodic behavior logistics analysis model to analyze whether the target logistics order satisfies the activity periodic behavior. It can be understood that when judging whether the target logistics order satisfies the activity periodic behavior, the target logistics order may be a completed order or an ongoing order. Taking the example that the target logistics order has been completed and the activity periodic behavior is the order processing cycle, the analysis of whether the target logistics order satisfies the activity periodic behavior based on the logistics analysis model is specifically explained:

[0066] Specifically, at this time, the order processing cycle of the target logistics order can be obtained first, for example, the order processing cycle is 7 days, and then the order processing cycle of the target logistics order is predicted based on the activity periodic behavior logistics analysis model, assuming it is 8 days. At this time, the actual processing cycle is compared with the predicted processing cycle. When the actual processing cycle meets the preset processing cycle, it is considered that the target logistics order meets the activity periodic behavior. In one example, when the difference between the actual processing cycle and the preset processing cycle is less than 2 days, it is considered that the actual processing cycle meets the preset processing cycle.

[0067] Furthermore, in other examples, ARIMA (Autoregressive Integrated Moving Average) or state space models (such as Kalman filter) can also be used to analyze the activity periodic behavior of the target logistics orders.

[0068] Further, the target node may include but is not limited to the target scan type, the target time period and the target remark information, wherein the target scan type may be warehousing, outbound, transshipment, etc., the target time period may be a specific date range, working days, weekends, etc., and the target remark information may be special processing requirements, abnormal remark, etc.; when the target node includes the three, based on the target node, the transshipment trend of the target logistics order can be analyzed by first collecting multiple data corresponding to the above three target nodes of the target logistics order, further arranging the data in chronological order to form time series data, and further using the time series decomposition method (such as STL decomposition) to decompose the time series into trend, seasonality and residual components. Further analyze the trend component therein to identify the long-term change trend in the data. It can be understood that the trend component represents the long-term change trend, the seasonal component represents the periodic change, and the residual component represents the random fluctuation. In this example, only the trend component is analyzed.

[0069] Furthermore, when the target node includes these three, based on the target node, analyzing the abnormal transportation behavior of the target logistics order can be, first, collecting multiple data corresponding to the above three target nodes of the target logistics order, selecting a suitable anomaly detection method, such as a machine learning algorithm (such as Isolation Forest, One-Class SVM), etc., and identifying abnormal points in the transportation time, delay time, and abnormal events through the anomaly detection method.

[0070] S110. Determine the logistics control mechanism of the target order based on the logistics behavior.

[0071] In one example, when it is determined that a given logistics behavior is an abnormal signature, an abnormal signature text message can be sent to the user, or the user can be called to verify. When it is verified that the target logistics order is indeed an abnormal signature, redelivery can be arranged immediately to ensure that the customer receives the correct package as soon as possible, and based on the specific circumstances of the abnormal signature, corresponding customer compensation can be provided, such as refunds, coupons, gifts, etc., to improve customer satisfaction.

[0072] When it is determined that the logistics behavior is stagnant for a long time, a detention SMS can be sent to the user to remind the user to pick up the item in time. It can be understood that this application can predict the transfer trend and abnormal behavior of the target logistics, facilitate the planning of the logistics scheduling mechanism in advance, and reduce the risks and losses in the logistics process.

[0073] It can be understood that the above logistics control mechanism is flexibly determined based on logistics behavior. The above is only an exemplary description and does not exhaustively list logistics behavior and corresponding logistics control mechanisms.

[0074] S112. Control the target order based on the logistics control mechanism.

[0075] It can be understood that this embodiment can combine the current logistics trajectory and current business needs to realize the logistics behavior control of the target logistics order, can adjust the logistics strategy and operation in real time, quickly respond to market changes and customer needs, and improve the flexibility and adaptability of logistics transportation; and, by setting the target node and its screening conditions, the present application can more accurately locate the key nodes of the order in the logistics process, help users quickly obtain relevant information, and improve decision-making efficiency; and, the present application can deeply analyze the logistics behavior of the target order, identify potential problems and bottlenecks, and then optimize the logistics process, improve overall efficiency, and can formulate targeted logistics control mechanisms based on the results of the logistics behavior analysis to meet different business needs and improve service quality and customer satisfaction; further, the embodiment of the present application can ensure that the target node of the target logistics order is highly consistent with the actual business needs by obtaining the correspondence between business needs, node information and screening conditions, thereby improving the pertinence and effectiveness of logistics management.

[0076] Furthermore, Figure 2 Another flow chart of the logistics order control method is used to introduce the establishment of a logistics analysis model before obtaining a logistics analysis model matching the target node. For details, refer to Figure 2 , the establishment of logistics analysis model can include the following steps:

[0077] S200. Obtain multiple sample logistics orders and sample logistics trajectory data corresponding to each sample logistics order.

[0078] The sample logistics order may be a historical logistics order within a target time period. The target time period may be set based on actual demand, and may be a week or a month. Specifically, the historical logistics orders within the target time period may be extracted from the enterprise's ERP system, logistics management system (TMS) or database. The sample logistics trajectory data corresponding to each sample logistics order may be obtained from the logistics management system (TMS), GPS tracking system or third-party logistics service provider. The sample logistics trajectory data may include but is not limited to timestamp, geographic location (latitude and longitude), status (such as loading, in transit, unloading, etc.) and other information.

[0079] S202: pre-process each sample logistics trajectory data to obtain a plurality of pre-processed trajectory data.

[0080] Specifically, the preprocessing of each sample logistics trajectory data can be performed by first checking the missing values ​​in the sample logistics trajectory data and processing them, such as filling the missing values ​​or deleting the missing data records, and further detecting and processing abnormal values, such as unreasonable time intervals, geographical location deviations, etc. Among them, the invalid data in the sample logistics trajectory data can be removed based on the missing value processing algorithm, and the abnormal characters or erroneous records in the data can be identified and removed based on the regular expression matching and denoising algorithms;

[0081] Further, timestamps in different formats are converted into a unified time format to ensure data consistency and unify the representation of geographic locations, such as converting different coordinate systems into a unified coordinate system (such as WGS84). Among them, time data in different formats can be unified into a specific standard format based on the time conversion function.

[0082] The trajectory data is further simplified, such as by using trajectory point clustering or trajectory line simplification algorithms to reduce the amount of data, and continuous trajectory points in the same state are aggregated to simplify the representation of trajectory data.

[0083] S204 , based on the model requirement, extracting a plurality of feature trajectory data matching the model requirement from the plurality of pre-processed trajectory data, and the feature trajectory data is used to match the target node.

[0084] Specifically, key features matching the target node can be extracted from the preprocessed trajectory data, for example, the target node of the target logistics order under the target business demand based on the one removed in step S102 before establishing the logistics analysis model.

[0085] S206. Determine a logistics analysis model based on multiple feature trajectory data.

[0086] Specifically, multiple feature trajectory data corresponding to multiple historical logistics orders are grouped to obtain a training group, a test group, and a verification group. The logistics analysis model is trained using the feature trajectory data corresponding to the training group, and the test and verification are performed based on the feature trajectory data corresponding to the test group and the verification group, respectively, to improve the accuracy and generalization ability of the logistics analysis model. It can be understood that matching the logistics analysis model with the target node can enable the trained logistics analysis model to more accurately analyze the logistics behavior when analyzing the target logistics order in the later stage, thereby improving the accuracy of logistics behavior analysis.

[0087] Furthermore, Figure 3 is another flow chart of the logistics order control method, which is applied when the target node includes the target scanning type, target time period and target remark information. For details, refer to Figure 3 , the method further comprises:

[0088] S300: Determine the status information of the target logistics order based on the target scanning type and the target remark information.

[0089] In one example, the status information may include a proxy signing status or a reverse logistics status. When the status information is a proxy signing status, step S302 is executed; when the status information is a reverse logistics status, step S304 is executed.

[0090] S302. When the status information is the proxy signing status, remove the secondary delivery mark.

[0091] It is understandable that when the status information is a signed-for status, it means that the goods corresponding to the target logistics order have been signed for by someone else. At this time, removing the secondary delivery mark can avoid the need for re-delivery, reducing unnecessary repeated deliveries and improving delivery efficiency.

[0092] S304: When the status information is a reverse logistics status, mark the reverse transportation time of the target logistics order.

[0093] It is understandable that when the status information is a reverse logistics status, it means that the goods corresponding to the target logistics order may be rejected or returned. At this time, the reverse transportation time of the target logistics order can be marked and the real-time return status of the order can be monitored.

[0094] This application embodiment can determine the status information of the target logistics order based on the target scanning type and the target remark information, and remove the secondary delivery mark when the status information is the proxy signing status, which can reduce unnecessary delivery and information interference, optimize the delivery process, and improve logistics efficiency; and, when the status information is reverse logistics, marking the reverse logistics time can help logistics managers clearly understand the progress of reverse logistics, which is convenient for subsequent processing and tracking.

[0095] According to another aspect of the present application, a logistics order control device is also disclosed, specifically, as follows Figure 4 As shown, the logistics order control device includes:

[0096] The first acquisition module is used to acquire the target logistics order and the current logistics track corresponding to the target logistics order;

[0097] The second acquisition module acquires the target node of the target logistics order under the target business requirements and the screening conditions of the target node;

[0098] The filtering module is used to filter the target nodes of the target logistics order from the current logistics track based on the filtering conditions and display them to the user;

[0099] The third acquisition module is used to acquire a logistics analysis model matching the target node;

[0100] The logistics behavior analysis module is used to analyze the logistics behavior of the target logistics order based on the logistics analysis model and target nodes;

[0101] The logistics control mechanism determination module is used to determine the logistics control mechanism of the target order based on the logistics behavior;

[0102] The control module is used to control the target order based on the logistics control mechanism.

[0103] Furthermore, the second acquisition module includes:

[0104] A corresponding relationship acquisition unit, used to acquire the corresponding relationship between business requirements, node information and screening conditions;

[0105] The search unit is used to search for the target node of the target logistics order under the target business demand and the screening conditions of the target node based on the corresponding relationship.

[0106] Furthermore, the screening module is specifically used for:

[0107] Based on the dynamic filtering rule engine, the target node of the target logistics order is filtered out from the current logistics track and displayed to the user, wherein the dynamic filtering rule engine has filtering conditions written therein and the filtering conditions are editable in the dynamic filtering rule engine.

[0108] Furthermore, the device also includes:

[0109] A status information determination module, used to determine the status information of the target logistics order based on the target scanning type and the target remark information, wherein the status information includes the signing status or the reverse logistics status;

[0110] The mark removal module is used to remove the secondary delivery mark when the status information is the proxy signing status;

[0111] The time marking module is used to mark the reverse transportation time of the target logistics order when the status information is the reverse logistics status.

[0112] Furthermore, the device also includes:

[0113] A fourth acquisition module is used to acquire multiple sample logistics orders and sample logistics trajectory data corresponding to each sample logistics order;

[0114] A preprocessing module, used for preprocessing each sample logistics trajectory data to obtain a plurality of preprocessed trajectory data;

[0115] An extraction module is used to extract multiple feature trajectory data matching the model requirements from multiple pre-processed trajectory data based on model requirements, and the feature trajectory data is used to match the target node;

[0116] The model determination module is used to determine the logistics analysis model based on multiple feature trajectory data.

[0117] Furthermore, the preprocessing module includes:

[0118] An invalid data removal unit, used to remove invalid data in sample logistics trajectory data based on a missing value processing algorithm;

[0119] An identification and removal unit, used to identify and remove abnormal characters or erroneous records in the data based on regular expression matching and denoising algorithms;

[0120] The data unification unit is used to unify time data in different formats into a specific standard format based on a time conversion function.

[0121] Furthermore, the logistics behavior analysis module includes:

[0122] The first analysis unit is used to analyze whether the target logistics order meets the activity periodicity behavior based on the logistics analysis model;

[0123] The second analysis unit is used to analyze the transfer trend of the target logistics order and the abnormal transfer behavior of the target logistics order based on the target node.

[0124] 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.

[0125] According to another aspect of the present application, the present application also discloses an electronic device, which includes a memory and at least one processor, wherein instructions are stored in the memory; at least one processor calls the instructions in the memory so that the electronic device executes each step of the above logistics order control method.

[0126] above Figure 4 The grid warehouse billing device based on operating status 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.

[0127] Figure 5is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 500 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and a memory 520, and one or more storage media 530 (for example, one or more mass storage devices) storing application programs 533 or data 532. Among them, the memory 520 and the storage medium 530 can be short-term storage or permanent storage. The program stored in the storage medium 530 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 500. Furthermore, the processor 510 can be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the electronic device 500.

[0128] The electronic device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input and output interfaces 550, and / or one or more operating systems 531, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 5 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.

[0129] 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 logistics order control method.

[0130] 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.

[0131] 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.

[0132] 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 logistics order control method, characterized in that: The method comprises: Obtaining a target logistics order and a current logistics track corresponding to the target logistics order; Obtaining a target node of the target logistics order under a target business requirement and a screening condition of the target node; Based on the screening condition, the target node of the target logistics order is screened out from the current logistics track and displayed to the user; Acquire a logistics analysis model matching the target node; Based on the logistics analysis model and the target node, analyzing the logistics behavior of the target logistics order; Based on the logistics behavior, determining a logistics control mechanism for the target logistics order; The target order is controlled based on the logistics control mechanism.

2. The logistics order control method according to claim 1, characterized in that: The step of obtaining the target node of the target logistics order under the target business requirement and the screening condition of the target node includes: Obtain the correspondence between business requirements, node information, and screening conditions; Based on the corresponding relationship, the target node of the target logistics order under the target business demand and the screening conditions of the target node are searched.

3. The logistics order control method according to claim 1, characterized in that: The step of filtering out the target node of the target logistics order from the current logistics track based on the filtering condition and displaying the target node to the user includes: Based on a dynamic filtering rule engine, the target node of the target logistics order is filtered out from the current logistics track and displayed to the user, wherein the filtering conditions are written into the dynamic filtering rule engine and the filtering conditions are editable in the dynamic filtering rule engine.

4. The logistics order control method according to claim 1, characterized in that: The target node includes a target scanning type, a target time period and target remark information, and the method further includes: Based on the target scan type and the target remark information, determine the status information of the target logistics order, wherein the status information includes the signing status or the reverse logistics status; When the status information is a proxy signing status, remove the secondary delivery mark; When the status information is a reverse logistics status, the reverse transportation time of the target logistics order is marked.

5. The logistics order control method according to claim 1, characterized in that: Before obtaining the logistics analysis model, the method further includes establishing the logistics analysis model, including: Obtain multiple sample logistics orders and sample logistics trajectory data corresponding to each of the sample logistics orders; Preprocessing each of the sample logistics trajectory data to obtain a plurality of preprocessed trajectory data; Based on the model requirement, extracting a plurality of feature trajectory data matching the model requirement from the plurality of pre-processed trajectory data, wherein the feature trajectory data is used to match the target node; Based on the plurality of characteristic trajectory data, the logistics analysis model is determined.

6. The logistics order control method according to claim 5, characterized in that: The preprocessing of each sample logistics trajectory data to obtain a plurality of preprocessed trajectory data includes: Removing invalid data from the sample logistics trajectory data based on a missing value processing algorithm; Identify and remove abnormal characters or erroneous records in data based on regular expression matching and denoising algorithms; Based on the time conversion function, time data in different formats are unified into a specific standard format.

7. The logistics order control method according to claim 1, characterized in that: The logistics behavior includes activity periodicity behavior, transfer trend and transfer abnormality behavior. The logistics behavior of the target logistics order analyzed based on the logistics analysis model and the target node includes: Based on the logistics analysis model, analyzing whether the target logistics order meets the activity periodicity behavior; Based on the target node, the transfer trend of the target logistics order and the abnormal transfer behavior of the target logistics order are analyzed.

8. A logistics order control device, characterized in that: The device comprises: A first acquisition module is used to acquire a target logistics order and a current logistics track corresponding to the target logistics order; A second acquisition module is used to acquire a target node of the target logistics order under a target business requirement and a screening condition of the target node; A screening module, used for screening the target node of the target logistics order from the current logistics track based on the screening condition and displaying it to the user; The third acquisition module is used to acquire the logistics analysis model; A logistics behavior analysis module, used to analyze the logistics behavior of the target logistics order based on the logistics analysis model and the target node; A logistics control mechanism determination module, used to determine the logistics control mechanism of the target order based on the logistics behavior; A control module is used to control the target order based on the logistics control mechanism.

9. An electronic device, characterized in that: The electronic device 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 logistics order control method as claimed in 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 logistics order control method as described in any one of claims 1-7 are implemented.

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