Logistics node circulation information acquisition method and device and computer device

Abstract

The application provides a logistics node circulation information acquisition method and device, computer equipment and a storage medium. The target waybills in an observation node are acquired; the waybill retention time length approximate data of the observation node is acquired according to the presence time length of each target waybill; and the circulation information of the observation node is determined according to the waybill retention time length reference data of the observation node, the waybill retention time length approximate data and the waybill quantity of the target waybill. When the circulation information of the observation node is acquired, the current waybill retention conditions such as the waybill quantity and the waybill retention time length approximate data of the target waybill in the observation node are considered, and the historical waybill retention conditions corresponding to the retention time length reference data are also considered, thereby effectively improving the accuracy of judging whether the observation node is a logistics node with abnormal circulation, and realizing rapid positioning of the abnormal circulation node.

Description

Technical Field

[0001] This application relates to the field of big data technology, specifically to a method, apparatus, and computer device for acquiring logistics node circulation information, wherein the computer device includes computer equipment and computer-readable storage medium (hereinafter referred to as storage device). Background Technology

[0002] In the logistics and transportation process, the transportation capacity of logistics nodes is limited. When encountering emergencies such as a surge in express delivery orders, manpower shortages, or major natural disasters, express delivery orders are prone to be delayed. The delay of express delivery orders leads to abnormal circulation information at logistics nodes. Since both the delay of express delivery orders and the abnormal circulation information at logistics nodes rely on staff reporting, there are often information delays or gaps, making it impossible to detect abnormal delays of express delivery orders in a timely manner. In severe cases, this can lead to warehouse overload and result in high economic losses. Summary of the Invention

[0003] Therefore, it is necessary to provide a method, device, computer equipment, and storage medium for obtaining logistics node circulation information to quickly locate abnormal circulation nodes, in order to address the above-mentioned technical problems.

[0004] Firstly, this application provides a method for obtaining logistics node circulation information, the method comprising:

[0005] Obtain the target waybill within the observation node;

[0006] Based on the on-site duration of each target waybill, approximate data on the waybill dwell time of the observation node are obtained;

[0007] Based on the baseline data of waybill dwell time at the observation node, the approximate data of waybill dwell time, and the number of waybills for the target waybill, the circulation information of the observation node is determined.

[0008] In some embodiments of this application, the flow information of the observation node is determined based on the baseline data of the waybill dwell time, the approximate data of the waybill dwell time, and the number of waybills for the target waybill, including:

[0009] The node type of the observation node is determined based on the baseline data of the waybill dwell time of the observation node;

[0010] If the node type of the observed node is the original node category, the dwell time growth information of the observed node is determined based on the approximate data of the waybill dwell time and the baseline data of the waybill dwell time.

[0011] Based on the approximate data of waybill dwell time, dwell time growth information, and waybill quantity of the observation nodes, the circulation information of the observation nodes is determined.

[0012] In some embodiments of this application, based on approximate data of waybill dwell time, dwell time growth information, and the number of waybills at the observation node, the circulation information of the observation node is determined, including:

[0013] If the number of waybills in the target waybill exceeds the waybill volume threshold, the approximate data of the waybill's dwell time exceeds the dwell time threshold, and the dwell time growth information exceeds the preset growth threshold, the circulation information of the observation node is considered abnormal circulation information.

[0014] In some embodiments of this application, approximate data on the dwell time of waybills at observation nodes are obtained based on the on-site duration of each target waybill, including:

[0015] The target waybills are sorted according to their on-site time, and the target percentile time at different percentiles is obtained.

[0016] The target quantile duration at the preset percentile is determined as an approximate data of the waybill dwell time at the observation node.

[0017] In some embodiments of this application, before determining the flow information of the observation node based on the baseline data of the waybill dwell time, the approximate data of the waybill dwell time, and the number of waybills of the target waybill, the following steps are included:

[0018] Obtain historical waybills for the observed nodes at historical observation time points;

[0019] The historical waybills are sorted according to their on-site duration, and the historical percentile duration at different percentiles is obtained.

[0020] The historical percentile duration at the preset percentile is determined as the baseline data for the waybill dwell time at the observation node.

[0021] In some embodiments of this application, the information on the increase in dwell time includes the increase value of dwell time and the increase factor of dwell time;

[0022] Based on approximate data of waybill dwell time and baseline data of waybill dwell time, the dwell time growth information of the observed nodes is determined, including:

[0023] In the approximate data of waybill dwell time and the baseline data of waybill dwell time, the dwell time growth value of the observation node is determined based on the difference between the target quantile time and the historical quantile time at the same preset percentile.

[0024] The dwell time growth factor of the observation node is determined by the ratio of the target quantile duration to the historical quantile duration at the same preset percentile.

[0025] In some embodiments of this application, the flow information of the observation node is determined based on the baseline data of the waybill dwell time, the approximate data of the waybill dwell time, and the number of waybills for the target waybill, including:

[0026] The node type of the observation node is determined based on the baseline data of the waybill dwell time of the observation node;

[0027] If the node type of the observed node is a newly added node category, the circulation information of the observed node is determined based on the approximate data of the number of waybills and the dwell time of waybills.

[0028] In some embodiments of this application, based on approximate data of waybill dwell time, dwell time growth information, and the number of waybills at the observation node, the circulation information of the observation node is determined, including:

[0029] If the number of waybills in the target waybill exceeds the waybill volume threshold and the approximate waybill dwell time exceeds the dwell time threshold, the circulation information of the observation node is considered abnormal circulation information.

[0030] Secondly, this application provides a device for acquiring logistics node circulation information, the device comprising:

[0031] The target waybill acquisition module is used to acquire target waybills within the observation node;

[0032] The on-site duration acquisition module is used to obtain approximate data on the on-site duration of each target waybill, based on the on-site duration of each waybill.

[0033] The circulation information acquisition module is used to determine the circulation information of the observation node based on the baseline data of the waybill dwell time, the approximate data of the waybill dwell time, and the number of waybills of the target waybill.

[0034] Thirdly, this application also provides a server, the server comprising:

[0035] One or more processors;

[0036] Memory; and

[0037] One or more applications, wherein the applications are stored in memory and configured to be executed by a processor to implement a method for acquiring logistics node flow information.

[0038] Fourthly, this application also provides a computer-readable storage medium storing a computer program thereon, which is loaded by a processor to execute steps in a method for obtaining logistics node circulation information.

[0039] Fifthly, embodiments of this application provide a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method provided in the first aspect described above.

[0040] The aforementioned method, apparatus, computer equipment, and storage medium for acquiring logistics node circulation information involve: acquiring target waybills within the observation node; obtaining approximate waybill dwell time data for the observation node based on the on-site duration of each target waybill; and determining the circulation information of the observation node based on the baseline data of waybill dwell time, the approximate data of waybill dwell time, and the number of target waybills. In acquiring the circulation information of the observation node, both the current waybill dwelling situation, such as the number of target waybills and the approximate waybill dwell time data, and the historical waybill dwelling situation corresponding to the baseline data of dwell time are considered. This effectively improves the accuracy of determining whether an observation node is a logistics node with abnormal circulation, and enables rapid location of nodes with abnormal circulation. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram of a scenario illustrating the method for obtaining logistics node circulation information in an embodiment of this application;

[0043] Figure 2 This is a flowchart illustrating the method for obtaining logistics node circulation information in an embodiment of this application;

[0044] Figure 3 This is a flowchart illustrating the steps for obtaining approximate data on the dwell time of waybills in an embodiment of this application;

[0045] Figure 4 This is a flowchart illustrating the steps for obtaining circulation information of the observation node in an embodiment of this application;

[0046] Figure 5 This is a flowchart illustrating the flow information acquisition steps of another observation node in an embodiment of this application;

[0047] Figure 6 This is a flowchart illustrating another method for obtaining logistics node circulation information in this application embodiment;

[0048] Figure 7 This is a schematic diagram of the structure of the device for acquiring logistics node circulation information in the embodiments of this application;

[0049] Figure 8 This is a schematic diagram of the structure of the computer device in the embodiments of this application. Detailed Implementation

[0050] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0051] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0052] In the description of this application, the word "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0053] In the embodiments of this application, it should be noted that the method for obtaining logistics node circulation information provided in this application is executed in a computer device. The processing objects of each computer device exist in the form of data or information, such as time, which is essentially time information, so that the computer device can process it. The specifics will not be elaborated here.

[0054] In this embodiment of the application, it should also be noted that the method for obtaining logistics node circulation information provided in this embodiment of the application can be applied to, for example, Figure 1The system shown is for acquiring logistics node circulation information. This system includes a terminal 100 and a server 200. The terminal 100 can be a device that includes both receiving and transmitting hardware, meaning it has hardware capable of performing bidirectional communication over a two-way communication link. Specifically, the terminal 100 can be a desktop or mobile terminal installed at different logistics transportation points. It can also be a mobile phone, tablet, laptop, or a camera installed at the monitoring site for information collection, storage, and transmission. The server 200 can be a standalone server, a server network, or a server cluster, including but not limited to computers, network hosts, single network servers, multiple network server sets, or cloud servers composed of multiple servers. The cloud server consists of a large number of computers or network servers based on cloud computing.

[0055] Those skilled in the art will understand that Figure 1 The application environment shown is merely one application scenario of the solution in this application and does not constitute a limitation on the application scenario of the solution in this application. Other application environments may include those that are more specific to this application. Figure 1 The number of computer devices shown is more or less, for example Figure 1 Only one server 200 is shown in the diagram. It is understandable that the system for acquiring logistics node circulation information may include one or more other servers; specific details are not specified here. Additionally, as... Figure 1 As shown, the logistics node circulation information acquisition system may also include a storage device for storing data, such as waybill snapshots, transportation-related data, etc.

[0056] It should also be noted that, Figure 1 The schematic diagram of the logistics node circulation information acquisition system shown is merely an example. The logistics node circulation information acquisition system and scenario described in this embodiment of the invention are for the purpose of more clearly illustrating the technical solutions of this embodiment of the invention, and do not constitute a limitation on the technical solutions provided by this embodiment of the invention. As those skilled in the art will know, with the evolution of the logistics node circulation information acquisition system and the emergence of new business scenarios, the technical solutions provided by this embodiment of the invention are also applicable to similar technical problems.

[0057] See Figure 2 This application provides a method for obtaining logistics node circulation information, which is mainly applied to the above-mentioned... Figure 1 Taking server 200 as an example, the method includes steps S210 to S230, as follows:

[0058] S210, obtain the target waybill within the observation node.

[0059] Among them, the observation node refers to the logistics point where circulation information is to be acquired. The logistics node refers to any node that carries out the transfer, distribution and storage of express delivery orders. It can be a certain distribution network point, a certain logistics transfer point, etc. The target order can refer to all orders that are stuck at the observation node (i.e., a certain logistics transportation node). Furthermore, it can also refer to orders that are stuck at the observation node and belong to the same granularity. For example, orders of the same granularity refer to orders that are in the same link in a certain logistics network point, belong to the same product type, have the same snapshot time and / or flow to the same place. The link can include the transfer link, the delivery link, etc.

[0060] Specifically, the method for obtaining logistics node circulation information provided in this application embodiment can be applied to application scenarios that require anomaly prediction of circulation information at different logistics nodes. The setting of the target waybill depends on the actual business needs of the application scenario. Before the server 200 executes the task of obtaining circulation information, the terminal 100 set at the logistics node collects the target waybill, and then uploads the target waybill and its related data information to the server 200. The server 200 then obtains the logistics node circulation information based on the target waybill and its data information. Alternatively, the terminal 100 set at the logistics node can be a camera with a camera function. The terminal 100 periodically takes pictures of the local waybills to obtain waybill snapshots, and uploads the waybill snapshots to the server 200. The server 200 then obtains the target waybill and its related data information from the obtained waybill snapshots, and then obtains the logistics node circulation information based on the obtained target waybill and its related data information.

[0061] Specifically, the server can be set to a fixed observation time point, and upon reaching the observation time point, it can obtain the target waybill within the observation node.

[0062] Further, in one embodiment, obtaining the target waybill within the observation node includes: obtaining snapshots of all waybills within the observation node; and filtering out the on-site waybill snapshots based on the waybill operation information in the waybill snapshots to obtain the target waybill. Specifically, after obtaining the waybill snapshots, the server obtains the waybill operation information from the waybill snapshots. For example, it can identify the corresponding waybill operation information from the waybill snapshots through text recognition, or it can identify the corresponding waybill number from the waybill snapshots and then obtain the corresponding operation information from the operation code set, wherein the operation code set includes a set of waybill numbers that have been transported to the next node. Then, the server determines the on-site status of the waybill corresponding to the waybill snapshot based on the waybill operation information, and performs cancellation processing on waybills that have already flowed out of the current site or have been transferred to the next site to obtain the waybill that is still in the site corresponding to the observation node, i.e., the target waybill.

[0063] S220: Based on the on-site time of each target waybill, obtain approximate data on the waybill dwell time of the observation node.

[0064] The on-site duration refers to the length of time a target waybill remains at the observation node. Specifically, in one embodiment, the step of obtaining the on-site duration of a target waybill includes: determining the entry time of the target waybill from its waybill operation information; and obtaining the on-site duration of the target waybill based on the current observation time and the entry time of the target waybill. The waybill operation information includes the entry time of the waybill arriving at the observation node. After obtaining the entry time of the target waybill, the difference between the entry time and the current time is determined as the on-site duration of the target waybill.

[0065] Among them, the approximate data on waybill dwell time is a comprehensive description of the online time of target waybills in the observation node. It can be a statistical measure of the maximum or average on-site time of all target waybills in the observation node, which is subsequently used to predict the circulation information of the observation node. Specifically, the server obtains the on-site time corresponding to all target waybills and performs statistics on the on-site time of each target waybill to obtain on-site time thresholds corresponding to different preset percentages of target waybills, thereby obtaining approximate data on waybill dwell time corresponding to different preset percentages of target waybills.

[0066] Specifically, the server can obtain the on-site duration of all target waybills, sort the target waybills according to their on-site duration, and obtain a threshold for the on-site duration of the top 50% of target waybills. Then, based on the obtained threshold, approximate data for the waybill dwell time can be determined. For example, if the target waybills are sorted from smallest to largest on-site duration, the maximum value (threshold) for the top 50% of target waybills is 5 hours, meaning that 50% of the target waybills have an on-site duration of less than 5 hours. Similarly, if the target waybills are sorted from smallest to largest on-site duration, the minimum value (threshold) for the top 75% of target waybills is 7.4 hours, meaning that 75% of the target waybills have an on-site duration of less than 7.4 hours. Therefore, 5 hours (corresponding to the 50th percentile) and 7.4 hours (corresponding to the 75th percentile) can be determined as approximate data for the waybill dwell time of the observation nodes corresponding to different percentiles.

[0067] Further, in one embodiment, step 220 includes: S310, sorting each target waybill according to its on-site duration, and obtaining the target quantile duration at different percentiles; S320, determining the target quantile duration at the preset percentile as approximate data of the waybill dwell time of the observation node.

[0068] The target quantile time refers to the on-site time value at the n% (n≥0) position after sorting the on-site time of all target orders. The target quantile time at different percentiles corresponds to the critical value of the first preset percentage of target orders, that is, the online time threshold. For example, the target quantile time at the 50th percentile represents the on-site time threshold of the first 50% of target orders, that is, 50% of the target orders have an on-site time within this on-site time threshold. As another example, the target quantile time at the 75th percentile represents the on-site time threshold of the first 75% of target orders, that is, 75% of the target orders have an on-site time within this on-site time threshold.

[0069] Specifically, as described above, the server sorts target waybills based on their on-site duration and obtains the target quantile duration at each percentile. Then, based on the target quantile duration at each percentile, it determines the on-site duration threshold for the top preset percentage of target waybills. Finally, based on the obtained on-site duration threshold, it determines approximate data for the waybill dwell time at the observation node. It can be understood that the approximate waybill dwell time data for the observation node includes the target quantile duration at different preset percentiles, such as the target quantile duration at the 75th percentile and the target quantile duration at the 50th percentile. By using the quantile duration at different percentiles as approximate data for the waybill dwell time at the observation node, and using this data as an indicator to characterize the flow of the observation node, it facilitates the monitoring of waybill dwell times and the flow information of the observation node, thereby improving the monitoring capability of the flow information of the observation node.

[0070] S230: Based on the baseline data of waybill dwell time of the observation node, the approximate data of waybill dwell time, and the number of waybills of the target waybill, determine the circulation information of the observation node.

[0071] Among them, the reference data for waybill dwell time refers to the approximate data of waybill dwell time at historical observation points. Specifically, the method for obtaining the reference data for waybill dwell time is similar to that for the approximate data, the only difference being the data processing object. The data processing object for the reference data for waybill dwell time is the relevant data of waybills obtained at historical observation times, while the data processing object for the approximate data for waybill dwell time is the relevant data of waybills obtained at the current observation time.

[0072] Specifically, in one embodiment, the step of obtaining the reference data for waybill dwell time includes: obtaining historical waybills of the observation node at historical observation time points; sorting each historical waybill according to the on-site time of each historical waybill, and obtaining the historical quantile time at different percentiles; and determining the historical quantile time at the preset percentile as the reference data for waybill dwell time of the observation node.

[0073] Historical waybills refer to waybills that were stuck at the observation node at the time of the observation. This means that historical waybills and target waybills are waybills at the same granularity. For example, a target waybill is a waybill that is in transit, has a document type, and flows from location A to location B at the time of the current observation. Similarly, a historical waybill is a waybill that is in transit, has a document type, and flows from location A to location B at the time of the previous observation. Specifically, the server sorts the target waybills based on their historical on-site duration and obtains the historical percentile duration at each percentile. Then, based on the historical percentile duration at each percentile, it determines the on-site duration threshold for the previous preset percentage of historical waybills. Finally, based on the obtained on-site duration threshold, it determines the baseline data for the waybill dwell time at the observation node. It is understandable that the baseline data of waybill dwell time at the observation node includes the time spent at the target quantile at different preset percentiles. For example, it may include the historical time spent at the 75th percentile and the historical time spent at the 50th percentile. The baseline data of waybill dwell time and the approximate data of waybill dwell time are in one-to-one correspondence, that is, both include the time spent at the same percentile.

[0074] Furthermore, in one embodiment, there are multiple historical observation time points. Specifically, a historical observation time point can refer to the same time point within a historical observation period, where the observation period can be one week, one month, etc. Taking a one-week observation period as an example, if the current observation time point is October 14th, Thursday, historical observation time points can include Thursdays from the previous three weeks, namely September 23rd, September 30th, and October 7th. After obtaining approximate data on waybill dwell time corresponding to multiple historical observation time points, a weighted average of these approximate data on waybill dwell time corresponding to historical observation time points can be obtained as the baseline data for waybill dwell time at the observation node.

[0075] Specifically, the server can determine the current status of waybill backlog at the observation node based on the number of target waybills and the dwell time of the target waybills at the observation node. It can also compare the current status of waybill backlog at the observation node with the historical data of waybill backlog at the observation node. Finally, by combining the current status of waybill backlog at the observation node with the comparison results with the historical data of the observation node, the server can confirm whether the observation node is a logistics node with abnormal circulation.

[0076] In one embodiment, step S230 includes: S410, determining the node type of the observation node based on the waybill dwell time baseline data of the observation node; S420, if the node type of the observation node is the original node category, determining the dwell time growth information of the observation node based on the waybill dwell time approximation data and the waybill dwell time baseline data; S430, determining the circulation information of the observation node based on the waybill dwell time approximation data, dwell time growth information and waybill quantity of the observation node.

[0077] The observation nodes are categorized into two types: original nodes and newly added nodes. Observation nodes classified as original nodes are logistics nodes with normal order volume at historical observation times. Observation nodes classified as newly added nodes are logistics nodes with few or no order volume at historical observation times. After obtaining the order delay duration baseline data for the observation nodes, the server can classify the observation nodes based on the value of this baseline data to determine their node type. Specifically, if the order delay duration baseline data for an observation node is not empty and falls within the valid baseline data range, then the observation node can be identified as an original node.

[0078] The information on the increase in dwell time describes the increase in the dwell time of waybills at the current observation node compared to historical observation time points. Specifically, the information on the increase in dwell time can include the increase value of dwell time and the increase factor of dwell time. The increase value of dwell time can be determined by the difference between the approximate dwell time data and the baseline dwell time data, and the increase factor of dwell time can be determined by the ratio between the approximate dwell time data and the baseline dwell time data.

[0079] Furthermore, in one embodiment, determining the dwell time growth information of the observation node based on the approximate data of the waybill dwell time and the baseline data of the waybill dwell time includes: determining the dwell time growth value of the observation node based on the difference between the target quantile time and the historical quantile time at the same preset percentile in the approximate data of the waybill dwell time and the baseline data of the waybill dwell time; and determining the dwell time growth multiple of the observation node based on the ratio of the target quantile time and the historical quantile time at the same preset percentile.

[0080] As mentioned above, the baseline data and approximate data of waybill dwell time include the quantile time at the same percentile, and they are in one-to-one correspondence. Therefore, when obtaining dwell time growth information, the difference between the target quantile time and the historical quantile time at the same preset percentile in the approximate data and the baseline data is calculated to obtain the dwell time growth value corresponding to the preset percentile. Similarly, the ratio of the target quantile time and the historical quantile time at the same preset percentile in the approximate data and the baseline data is obtained to get the dwell time growth multiple corresponding to the preset percentile. For example, the baseline data for waybill dwell time at the observation node includes the historical 75th percentile and the historical 50th percentile. Approximate data for waybill dwell time includes the target 75th percentile and the target 50th percentile. The difference between the target 75th percentile and the historical 75th percentile can be used to obtain the dwell time growth value corresponding to the 75th percentile. The ratio of the target 50th percentile and the historical 50th percentile can be determined as the dwell time growth multiple corresponding to the 50th percentile. By obtaining the corresponding dwell time growth information from the target 100th percentile and historical 100th percentile at different percentiles, and using this information as an indicator of the flowability of the observation node, abnormal information such as a surge in logistics volume or dwell time can be quickly identified, effectively improving the monitoring capability of the flow information at the observation node.

[0081] The approximate data on the number of target waybills and their dwell time characterize the basic information of waybill dwell time at the current observation point in the observation node. The information on the increase in dwell time characterizes the horizontal comparison between the current dwell time and historical dwell time at the observation node, i.e., the increase in dwell time at the current observation point. When the observation node is the original node, by combining the approximate data on the number of target waybills, their dwell time, and the increase in dwell time, the basic information and increase in the dwell time of the observation node's waybills are confirmed to indicate whether the observation node's circulation information is abnormal, thus effectively improving the accuracy of the circulation information at the observation node.

[0082] Furthermore, in one embodiment, the circulation information of the observation node is determined based on the approximate data of the waybill dwell time, the dwell time growth information, and the number of waybills. This includes: if the number of waybills of the target waybill is greater than the waybill quantity threshold, the approximate data of the waybill dwell time is greater than the dwell time threshold, and the dwell time growth information is greater than the preset growth threshold, the circulation information of the observation node is circulation abnormal information.

[0083] As mentioned above, the number of target waybills and the approximate data of waybill dwell time represent the basic information of waybill dwell status at the current observation time point in the observation node. When the number of waybills is greater than the waybill volume threshold and the approximate data of waybill dwell time is greater than the dwell time threshold, it indicates that the number of waybills at the current observation time point in the observation node is large and the dwell time of waybills at the observation node is long, and there is a possibility that the number of waybills in the dwell exceeds the transportation capacity of the observation node. The information on the growth of waybill dwell time represents the growth information of waybill dwell status at the current observation time point in the observation node compared with the waybill dwell status at historical observation time points. When the growth information of waybill dwell time exceeds the preset growth threshold, it indicates that compared with historical observation time points, the growth of waybill volume in the observation node may exceed the preset elastic adjustment range of the observation node. Therefore, if the number of waybills in the target waybill is greater than the waybill volume threshold, the approximate data of the waybill dwell time is greater than the dwell time threshold, and the dwell time growth information is greater than the preset growth threshold, and the number of waybills in the observation node is large, the waybill dwell time in the observation node is long, and the transportation capacity of the observation node cannot bear the current number of waybills, then the observation node is determined to be a node with abnormal circulation.

[0084] Understandably, if any one of the following conditions is met: the number of target waybills is less than or equal to the waybill volume threshold, the approximate waybill dwell time is less than or equal to the dwell time threshold, or the dwell time growth information is less than or equal to the preset growth threshold, then the observation node is determined to be a node with normal circulation. For example, if the dwell time growth information is greater than the preset growth threshold, but the number of target waybills is less than or equal to the waybill volume threshold, or the approximate waybill dwell time is less than or equal to the dwell time threshold, it indicates that although the waybill volume in the observation node has increased significantly compared to historical observation points, the overall waybill volume and waybill dwell time are still within the transport capacity of the observation node.

[0085] Furthermore, in the logistics field, when encountering periods of surge in logistics order volume (such as shopping festivals), temporary logistics nodes are added to alleviate the transportation pressure on surrounding orders. However, there is no historical data for the newly added logistics nodes, making it impossible to make a horizontal comparison with the historical order retention situation of the observed nodes. Therefore, in one embodiment, step S230 includes: S510, determining the node type of the observed node based on the order retention time benchmark data of the observed node; S520, if the node type of the observed node is the newly added node category, determining the circulation information of the observed node based on the number of orders and the approximate order retention time data.

[0086] As mentioned above, the number of target waybills and the approximate data of waybill dwell time represent the basic information of waybill dwell time at the current observation point in the observation node. Since the observation node is a newly added node, there is no waybill dwell time to refer to at the historical observation point. Therefore, the basic information of waybill dwell time, such as the number of target waybills and the approximate data of waybill dwell time, is used to confirm whether the observation node is a logistics node with abnormal circulation.

[0087] Specifically, in one embodiment, based on the approximate data of waybill dwell time, dwell time growth information, and waybill quantity of the observation node, the circulation information of the observation node is determined, including: if the number of waybills for the target waybill is greater than the waybill volume threshold and the approximate data of waybill dwell time is greater than the dwell time threshold, the circulation information of the observation node is circulation anomaly information. As mentioned above, when the number of waybills is greater than the waybill volume threshold and the approximate data of waybill dwell time is greater than the dwell time threshold, it indicates that the observation node has a large number of waybills at the current observation time and a long dwell time for waybills at the observation node, suggesting that the number of waybills in the dwell may exceed the transportation capacity of the observation node; when both the number of waybills for the target waybill and the approximate data of waybill dwell time are greater than the dwell time threshold are true, the circulation information of the observation node is circulation anomaly information.

[0088] The aforementioned method for obtaining logistics node circulation information involves acquiring target waybills within the observation node; obtaining approximate waybill dwell time data for the observation node based on the on-site duration of each target waybill; and determining the circulation information of the observation node based on the baseline data of waybill dwell time, the approximate data of waybill dwell time, and the number of target waybills. When acquiring the circulation information of the observation node, both the current waybill dwelling situation (such as the number of target waybills and approximate dwell time data) and the historical waybill dwelling situation corresponding to the baseline data of dwell time are considered. This allows for the determination of whether an observation node is a logistics node with abnormal circulation by combining the current waybill dwelling situation and the comparison results between the current and historical waybill dwelling situations. This effectively improves the accuracy of the circulation information of the observation node and enables rapid location of nodes with abnormal circulation.

[0089] In one embodiment, such as Figure 6 As shown, a method for obtaining logistics node circulation information includes:

[0090] S601, Obtain the historical waybill of the observation node at the historical observation time point;

[0091] S602, sort the historical waybills according to their on-site duration and obtain the historical percentile duration at different percentiles;

[0092] S603, the historical percentile duration at the preset percentile is determined as the baseline data for the waybill dwell time of the observation node;

[0093] S604, Obtain the target waybill within the observation node;

[0094] S605, sort the target waybills according to their on-site time and obtain the target percentile time at different percentiles;

[0095] S660 determines the target quantile duration at the preset percentile as an approximate data of the waybill dwell time at the observation node;

[0096] S607, Determine the node type of the observation node based on the baseline data of the waybill dwell time of the observation node; if the node type of the observation node is the original node type, execute S608; if the node type of the observation node is the newly added node type, execute S610.

[0097] S608. Based on the approximate data of waybill dwell time and the baseline data of waybill dwell time, determine the dwell time growth information of the observation node;

[0098] S609, Based on the approximate data of the waybill dwell time, the information on the increase in dwell time, and the number of waybills of the observation node, determine the circulation information of the observation node;

[0099] S610 determines the circulation information of the observation node based on approximate data of the number of waybills and the dwell time of waybills.

[0100] The above embodiments will be further illustrated below with a specific example:

[0101] 1. Obtain baseline data on waybill dwell time;

[0102] For each logistics node in the entire logistics network, the historical waybills of each logistics node are accumulated, and the historical waybills of each logistics node are segmented according to different historical observation time points and different waybill granularities. For example, for logistics node A, the historical waybills accumulated for this logistics node are segmented to include waybills that are in transit, whose product type is document, and which are destined for location B at 6 pm every Thursday (historical observation time point).

[0103] For any logistics node and any slice corresponding to a waybill, the waybills are sorted according to their on-site time and the historical quantile time at different percentiles is obtained. Then, the target quantile time at the preset percentile is determined as the benchmark data of waybill dwell time at the observation node. For example, the benchmark data of waybill dwell time includes the quantile time corresponding to the 75th percentile and the quantile time corresponding to the 50th percentile.

[0104] Taking logistics node A as an example, we accumulated historical waybills at three historical observation points: 6 PM on September 23, 2021 (Thursday), 6 PM on September 30, 2021 (Thursday), and 6 PM on October 7, 2021 (Thursday). These waybills were in transit, their product type was documents, and they were destined for location B (waybill granularity). Then, for the historical waybills at different historical observation points, we obtained the 75th percentile and 50th percentile quantile time for each historical observation point. These were used as the baseline data for waybill dwell time at that historical observation point. Finally, we obtained the 7th percentile and 50th percentile quantile time corresponding to the three different historical observation points. It is understandable that the method for obtaining the baseline data for dwell time is the same for any logistics node, any historical observation point, and any granularity of waybill, and will not be elaborated here.

[0105] 2. Obtain approximate data on the waybill dwell time at the observation nodes;

[0106] The observation node can be any logistics node in the entire logistics network. At the current observation time, the observation node is observed. First, the target waybills of different granularities at the current observation time are obtained. Specifically, the waybills that are still in the observation node are photographed to obtain waybill snapshots. Then, the presence of the waybill snapshots is judged. For waybill snapshots that have left the site or have been transferred to the next site, the waybill is cancelled. Only the waybill snapshots that are still in the observation node are left. The waybills of different granularities are determined from the remaining waybill snapshots.

[0107] For waybills of the same granularity, the on-site time of the target waybill is obtained, the waybills are sorted according to their on-site time, and the quantile time at different percentiles is obtained. Then, the target quantile time at the preset percentile is determined as the approximate data of the waybill dwell time of the observation node. For example, the approximate data of waybill dwell time includes the quantile time corresponding to the 75th percentile and the quantile time corresponding to the 50th percentile.

[0108] Taking logistics node A as an example, let's take the processing of waybills at the granularity of being in the transit stage, with the product type being documents, and destined for location B as an example. Assuming the observation time point is 6 pm on October 14, 2021 (Thursday), we obtain waybills at the granularity of being still at logistics node A after the observation time point, with the product type being documents and destined for location B as target waybills. We obtain the on-site time of the target waybills, sort the target waybills according to their on-site time, and obtain the target quantile time at the 75th percentile and 50th percentile. The approximate data of the waybill dwell time at the observation node includes the target quantile time at the 75th percentile and the target quantile time at the 50th percentile.

[0109] 3. Obtaining flow information from observation nodes;

[0110] After determining the approximate data of waybill dwell time (corresponding to different granularities) to the observation node, the dwell time baseline data of the same granularity is first matched. Based on the numerical value of the matched dwell time baseline data, the observation node is classified to determine the node type of the observation node. Specifically, if the waybill dwell time baseline data of the observation node is not empty and the waybill dwell time baseline data is within the valid baseline data range, the observation node can be determined as an original node; otherwise, the observation node is a newly added node.

[0111] For example, in the baseline data of waybill dwell time at the observation node, if any one of the following conditions is met: the historical quantile time at the 75th percentile is empty, the historical quantile time at the 50th percentile is empty, the historical quantile time at the 75th percentile is greater than 24, the historical quantile time at the 50th percentile is greater than 24, the historical quantile time at the 75th percentile is less than 0.5, or the historical quantile time at the 50th percentile is less than 0.5, then the observation node is a new node; otherwise, the observation node is an original node.

[0112] After obtaining the node type of the observation node, the flow information of the observation node is obtained according to different decision conditions based on different node types.

[0113] When the observation node is the original node, the dwell time growth information of the observation node is determined based on the approximate data of the waybill dwell time and the baseline data of the waybill dwell time; the circulation information of the observation node is determined based on the approximate data of the waybill dwell time, the dwell time growth information and the number of waybills.

[0114] Specifically, based on the baseline data and approximate data of waybill dwell time at the same percentile, the historical quantile time and target quantile time are used to obtain the dwell time growth rate and dwell time growth value at different percentiles; then, the transportation link corresponding to the target waybill is obtained, and the following corresponding decisions are made for target waybills belonging to different transportation links:

[0115] A. Transit Link: If the number of waybills > 500, the increase multiple of the delay time corresponding to the 75th percentile > 8, the increase multiple of the delay time corresponding to the 50th percentile > 8, and the approximate value of the delay time corresponding to the 75th percentile > 12, then the circulation information of the observation node is abnormal, and the observation node is an abnormal circulation node; otherwise, the circulation information of the observation node is normal, and the observation node is a normal circulation node.

[0116] B. Collection and delivery process: If the number of waybills > 100, the delay time growth multiple corresponding to the 75th percentile > 8, the delay time growth rate corresponding to the 50th percentile > 8, and the delay time growth value corresponding to the 75th percentile > 6, then the circulation information of the observation node is abnormal, and the observation node is an abnormal circulation node; otherwise, the circulation information of the observation node is normal, and the observation node is a normal circulation node.

[0117] When the observation node is the original node, the dwell time growth information of the observation node is determined based on the approximate data of the waybill dwell time and the baseline data of the waybill dwell time. Based on the approximate data of the waybill dwell time, the dwell time growth information, and the number of waybills, the circulation information of the observation node is determined. For example, for target waybills outputting different transportation stages, the following corresponding decisions are made:

[0118] A. Transit Link: If the number of waybills is >500, the approximate dwell time corresponding to the 75th percentile is >12, and the approximate dwell time corresponding to the 50th percentile is >6, and all of the above conditions are met, then the flow information of the observation node is abnormal flow information, and the observation node is an abnormal flow node; otherwise, the flow information of the observation node is normal flow information, and the observation node is a normal flow node.

[0119] B. Collection and delivery process: If the number of waybills is >100, the approximate dwell time corresponding to the 75th percentile is >12, and the approximate dwell time corresponding to the 50th percentile is >6, then the circulation information of the observation node is abnormal, and the observation node is an abnormal circulation node; otherwise, the circulation information of the observation node is normal, and the observation node is a normal circulation node.

[0120] After determining the flow information to the observation node, the target waybill corresponding to the transportation node with abnormal flow information can be stored so that staff can call it and check the reason for the waybill's delay. Furthermore, the approximate delay time data obtained by the observation node at this observation time point can be saved according to the corresponding granularity, so that it can be called as the benchmark data for delay time at future observation time points.

[0121] The acquisition of logistics node circulation information can solve the problems of passive and lagging management of circulation anomaly risks. It digitizes, onlineizes, and productizes the monitoring process of circulation anomaly information, enabling timely monitoring, timely detection, and timely resolution, effectively reducing information delays and information gaps. In addition, by using different logistics nodes across the entire network as observation nodes, circulation information of each logistics node can be quickly obtained, enabling rapid and accurate identification of anomaly nodes. In the event of anomalies such as a surge in shipments, manpower shortages, or major natural disasters, rapid detection and real-time dispatching can be implemented.

[0122] To better implement the method for obtaining logistics node circulation information provided in the embodiments of this application, this application also provides a device for obtaining logistics node circulation information, based on the method provided in the embodiments of this application. Figure 7 As shown, the logistics node circulation information acquisition device 700 includes:

[0123] The target waybill acquisition module 710 is used to acquire target waybills within the observation node;

[0124] The on-site duration acquisition module 720 is used to obtain approximate data on the dwell time of the observation nodes based on the on-site duration of each target waybill.

[0125] The circulation information acquisition module 730 is used to determine the circulation information of the observation node based on the baseline data of the waybill dwell time, the approximate data of the waybill dwell time, and the number of waybills of the target waybill.

[0126] In one embodiment, the circulation information acquisition module 730 is further configured to determine the node type of the observation node based on the reference data of the waybill dwell time of the observation node; if the node type of the observation node is the original node category, determine the dwell time growth information of the observation node based on the approximate data of the waybill dwell time and the reference data of the waybill dwell time; and determine the circulation information of the observation node based on the approximate data of the waybill dwell time of the observation node, the dwell time growth information, and the number of waybills.

[0127] In one embodiment, the circulation information acquisition module 730 is further configured to identify circulation anomaly information of the observation node when the number of waybills of the target waybill is greater than the waybill quantity threshold, the approximate data of the waybill dwell time is greater than the dwell time threshold, and the dwell time growth information is greater than the preset growth threshold.

[0128] In one embodiment, the on-site duration acquisition module 720 is further configured to sort each target waybill according to the on-site duration of the target waybill, and obtain the target quantile duration at different percentiles; and determine the target quantile duration at the preset percentile as approximate data of the waybill dwell time of the observation node.

[0129] In one embodiment, the device for acquiring logistics node circulation information further includes a baseline duration acquisition module, which is used to acquire historical waybills of the observation node at historical observation time points; sort each historical waybill according to the on-site duration of each historical waybill, and acquire the historical percentile duration at different percentiles; and determine the historical percentile duration at the preset percentile as the baseline data for the waybill dwell time of the observation node.

[0130] In one embodiment, the circulation information acquisition module 730 is further configured to determine the dwell time growth value of the observation node based on the difference between the target quantile time and the historical quantile time at the same preset percentile in the approximate data of the waybill dwell time and the baseline data of the waybill dwell time; and to determine the dwell time growth multiple of the observation node based on the ratio of the target quantile time and the historical quantile time at the same preset percentile.

[0131] In one embodiment, the circulation information acquisition module 730 is further configured to determine the node type of the observation node based on the reference data of the waybill dwell time of the observation node; if the node type of the observation node is a newly added node category, the circulation information of the observation node is determined to be circulation abnormal information based on the number of waybills and the approximate data of waybill dwell time.

[0132] In one embodiment, the circulation information acquisition module 730 is further configured to identify circulation anomalies in the observation node when the number of waybills in the target waybill is greater than the waybill quantity threshold and the approximate data of the waybill dwell time is greater than the dwell time threshold.

[0133] In the above embodiments, target waybills within the observation node are acquired; approximate waybill dwell time data for the observation node is obtained based on the on-site duration of each target waybill; and the circulation information of the observation node is determined based on the baseline data of waybill dwell time, the approximate data of waybill dwell time, and the number of target waybills. When acquiring the circulation information of the observation node, both the current waybill dwelling situation, such as the number of target waybills and the approximate waybill dwell time data, and the historical waybill dwelling situation corresponding to the baseline data of dwell time are considered. This allows for the determination of whether the observation node is a logistics node with abnormal circulation by combining the current waybill dwelling situation and the comparison results between the current waybill dwelling situation and the historical waybill dwelling situation, effectively improving the accuracy of the circulation information of the observation node and enabling rapid location of nodes with abnormal circulation.

[0134] In some embodiments of this application, the device 700 for acquiring logistics node circulation information can be implemented as a computer program, and the computer program can be implemented in, for example... Figure 8 The computer device shown runs on this computer. The computer device's memory can store various program modules that make up the information acquisition device 700 for this logistics node, for example, Figure 7 The target waybill acquisition module 710, the on-site duration acquisition module 720, and the circulation information acquisition module 730 are shown. The computer program comprised of these modules causes the processor to execute the steps in the logistics node circulation information acquisition methods described in the various embodiments of this application.

[0135] For example, Figure 8 The computer device shown can be used as follows Figure 7The target waybill acquisition module 710 in the logistics node circulation information acquisition device 700 shown executes step S210. The computer device can execute step S220 via the presence duration acquisition module 720. The computer device can execute step S230 via the circulation information acquisition module 730. The computer device includes a processor, memory, and network interface connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communication with external computer devices via a network connection. When the computer program is executed by the processor, it implements a method for acquiring logistics node circulation information.

[0136] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0137] In some embodiments of this application, a computer device is provided, including one or more processors; a memory; and one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor as described in the method for obtaining logistics node circulation information. The steps of the method for obtaining logistics node circulation information described here may be steps from the methods for obtaining logistics node circulation information described in the various embodiments above.

[0138] In some embodiments of this application, a computer-readable storage medium is provided, storing a computer program. The computer program is loaded by a processor, causing the processor to execute the steps of the method for obtaining logistics node circulation information described above. The steps of the method for obtaining logistics node circulation information here can be the steps in the methods for obtaining logistics node circulation information described in the various embodiments above.

[0139] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0140] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0141] The foregoing has provided a detailed description of a method, apparatus, computer device, and storage medium for obtaining logistics node circulation information provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for obtaining logistics node circulation information, characterized in that, include: Obtain the target waybill within the observation node; The target waybills are sorted according to their on-site duration to obtain the target quantile duration at different percentiles. The target quantile duration at the preset percentile is determined as the approximate data of the waybill dwell time at the observation node; Based on the baseline data of waybill dwell time at the observation node, the approximate data of waybill dwell time, and the number of waybills for the target waybill, the flow information of the observation node is determined, including: The node type of the observation node is determined based on the baseline data of the waybill dwell time of the observation node; If the node type of the observed node is the original node category, the dwell time growth information of the observed node is determined based on the approximate data of the waybill dwell time and the baseline data of the waybill dwell time; the circulation information of the observed node is determined based on the approximate data of the waybill dwell time, the dwell time growth information, and the number of waybills. If the node type of the observed node is a newly added node category, the circulation information of the observed node is determined based on the number of waybills and the approximate data of the waybill dwell time.

2. The method according to claim 1, characterized in that, The process of determining the flow information of the observation node based on the approximate data of the waybill dwell time, the information on the increase in dwell time, and the number of waybills includes: If the number of target waybills is greater than the waybill quantity threshold, the approximate data of waybill dwell time is greater than the dwell time threshold, and the dwell time growth information is greater than the preset growth threshold, the circulation information of the observation node is circulation anomaly information.

3. The method according to claim 1, characterized in that, Before determining the flow information of the observation node based on the baseline data of the waybill dwell time of the observation node, the approximate data of the waybill dwell time, and the number of waybills of the target waybill, the following steps are included: Obtain the historical waybills of the observation node at the historical observation time points; The historical waybills are sorted according to their on-site duration to obtain the historical percentile duration at different percentiles. The historical percentile duration at the preset percentile is determined as the baseline data for the waybill dwell time of the observation node.

4. The method according to claim 3, characterized in that, The information on the increase in dwell time includes the increase value of dwell time and the increase multiple of dwell time; The step of determining the dwell time growth information of the observation node based on the approximate data of the waybill dwell time and the baseline data of the waybill dwell time includes: In the approximate data of waybill dwell time and the baseline data of waybill dwell time, the dwell time growth value of the observation node is determined based on the difference between the target quantile time and the historical quantile time at the same preset percentile. The dwell time growth factor of the observation node is determined based on the ratio of the target quantile duration to the historical quantile duration at the same preset percentile.

5. The method according to claim 1, characterized in that, The process of determining the flow information of the observation node based on the number of waybills and the approximate dwell time of the waybills includes: If the number of target waybills is greater than the waybill quantity threshold and the approximate waybill dwell time is greater than the dwell time threshold, the circulation information of the observation node is circulation anomaly information.

6. A device for acquiring logistics node circulation information, characterized in that, The device includes: The target waybill acquisition module is used to acquire target waybills within the observation node; The on-site duration acquisition module is used to sort each target waybill according to the on-site duration of the target waybill, and obtain the target quantile duration at different percentiles; the target quantile duration at the preset percentile is determined as the approximate data of the waybill dwell time of the observation node. The circulation information acquisition module is used to determine the circulation information of the observation node based on the baseline data of the waybill dwell time of the observation node, the approximate data of the waybill dwell time, and the number of waybills of the target waybill, including: The node type of the observation node is determined based on the baseline data of the waybill dwell time of the observation node; If the node type of the observed node is the original node category, the dwell time growth information of the observed node is determined based on the approximate data of the waybill dwell time and the baseline data of the waybill dwell time; the circulation information of the observed node is determined based on the approximate data of the waybill dwell time, the dwell time growth information, and the number of waybills. If the node type of the observed node is a newly added node category, the circulation information of the observed node is determined based on the number of waybills and the approximate data of the waybill dwell time.

7. A computer device, characterized in that, The computer device includes: One or more processors; Memory; and One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the method for obtaining logistics node circulation information as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, It stores a computer program, which is loaded by a processor to execute the steps in the method for obtaining logistics node circulation information as described in any one of claims 1 to 5.

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