Logistics data analysis processing method and system

Abstract

The invention provides a logistics data analysis processing method and system, and belongs to the technical field of data processing, and the method specifically comprises the steps: determining the change condition of a distribution route of a logistics distribution order in a designated region according to the analysis result of order data of different dates, when the change condition of the distribution route of the logistics distribution order in the designated area meets the requirement, obtaining the distribution data of the freight vehicle in the adjacent area of the designated area, determining the date when the freight vehicle does not meet the requirement on the basis of the distribution data of the freight vehicle, the adjacent area and the order data in the designated area, and sending the determined date to the server; according to the invention, the logistics distribution order is used as the freight deviation date, and when the deviation condition of the freight vehicles at different freight deviation dates does not meet the requirement, the freight demand coefficient of the logistics distribution order in the specified area and the adjacent area is used to determine the distribution strategy of the freight vehicles in the specified area and the adjacent area, so that the transportation cost is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a logistics data analysis and processing method and system. Background Art

[0002] Logistics platform companies often use the order data obtained from different order users to optimize the scheduling of freight vehicles. However, in the actual scheduling process, there is often a technical problem that the distribution of freight vehicles and the distribution of orders do not match. This makes how to schedule freight vehicles based on the analysis results of order data a technical problem that needs to be solved urgently.

[0003] In order to realize the dispatching of freight vehicles, the invention patent application CN202411248136.4 "A bulk logistics transportation forecasting and dispatching optimization method based on data analysis" uses comprehensive analysis of multi-source data and the application of deep learning models to achieve the accuracy and real-time planning of logistics transportation routes, effectively reducing transportation costs, but there are the following technical problems: In the process of optimizing the dispatching of freight vehicles, there are large differences in the distribution of order users in different regions, and there are also large differences in the distribution of delivery routes of logistics orders of order users in different regions. This leads to large differences in the demand for freight vehicles in different regions. Therefore, if differentiated dispatching strategies cannot be generated based on the distribution of order users in different regions and the distribution of logistics orders, the matching between freight vehicles and logistics data cannot be improved.

[0004] In response to the above technical problems, the present invention provides a logistics data analysis and processing method and system. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: According to one aspect of the present invention, a logistics data analysis and processing method is provided.

[0006] A logistics data analysis and processing method, specifically comprising: S1 determines the order data of the logistics delivery orders on different dates based on the acquired data of the logistics delivery orders on different dates in the designated area, and when the freight demand coefficient of the logistics delivery orders in the designated area is determined to be within a preset range based on the order data on different dates, proceeds to the next step; S2 determines the change of the delivery route of the logistics delivery order in the designated area based on the analysis results of the order data of different dates, and when the change of the delivery route of the logistics delivery order in the designated area meets the requirements, proceeds to the next step; S3 obtains the distribution data of freight vehicles in the adjacent areas of the designated area, and determines the date on which the freight vehicles do not meet the requirements based on the distribution data of the freight vehicles, the adjacent areas and the order data in the designated area, and uses the date as the freight deviation date; S4: When the deviation of freight vehicles on different freight deviation dates does not meet the requirements, the freight demand coefficient of the logistics delivery orders in the designated area and the adjacent areas is used to determine the allocation strategy of the freight vehicles in the designated area and the adjacent areas.

[0007] The beneficial effects of the present invention are: By judging whether the deviation of freight vehicles on different freight deviation dates meets the requirements, the technical problem of inaccurate judgment of freight reliability caused by single consideration of freight demand in a designated area is avoided. The deviation of freight vehicles on different dates is determined based on the allocation data of freight vehicles in adjacent areas, which also lays the foundation for determining differentiated allocation strategies for freight vehicles in designated areas.

[0008] The freight demand coefficient of the logistics delivery orders in the designated area and the adjacent areas is used to determine the allocation strategy of freight vehicles in the designated area and the adjacent areas, thereby avoiding the technical problem of insufficient freight reliability due to freight vehicles not meeting the requirements. At the same time, by further combining the freight demand coefficient of the logistics delivery orders in the designated area and the adjacent areas, dynamic adjustment of the allocation quantity of freight vehicles in different areas according to the freight demand coefficients of different areas is achieved.

[0009] A further technical solution is that the acquisition data of the logistics delivery order is determined based on the order record data of the logistics delivery order of the logistics delivery platform.

[0010] A further technical solution is that the order data of the logistics delivery order includes the delivery quantity of the logistics delivery order.

[0011] A further technical solution is that the method for determining the freight demand coefficient of the logistics delivery order in the designated area is: Based on the order data of different dates, determine the delivery volume of the logistics delivery orders on different dates, and determine the total delivery volume of the logistics delivery orders on different dates according to the delivery volume of the logistics delivery orders on different dates; According to the total delivery volume of logistics delivery orders on different dates, determine the date when the total delivery volume is greater than the preset delivery volume threshold, and use it as the delivery demand date; The freight demand coefficient of the logistics delivery orders in the specified area is determined according to the quantity ratio of the delivery demand date.

[0012] A further technical solution is that the freight demand coefficient of the logistics delivery orders in the designated area takes a value range between 0 and 1, wherein the larger the freight demand coefficient of the logistics delivery orders in the designated area, the higher the freight demand level of the logistics delivery orders in the designated area.

[0013] A further technical solution is that the method for determining the allocation strategy of freight vehicles in the designated area and adjacent areas is: Determine the required number of freight vehicles in the designated area and adjacent areas based on the freight demand coefficient of logistics delivery orders in the designated area and adjacent areas; The allocation strategy of freight vehicles in the designated area and adjacent areas is determined according to the demand quantity.

[0014] A further technical solution is that the demand quantity of freight vehicles in the designated area is determined based on the product of the freight demand coefficient and a preset demand proportional factor, the specific freight demand coefficient and the product of the preset demand proportional factor determine the matching quantity of freight vehicles, and the matching quantity is used as the demand quantity of freight vehicles in the designated area.

[0015] In a second aspect, the present invention provides a computer system comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-mentioned logistics data analysis and processing method when running the computer program.

[0016] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0019] Figure 1 It is a flow chart of a logistics data analysis and processing method; Figure 2 is a flow chart of a method for determining a freight demand coefficient for a logistics delivery order in a specified area; Figure 3 It is a flow chart for determining whether the changes in the delivery routes of logistics delivery orders in a specified area meet the requirements; Figure 4 is a flow chart of a method for determining a freight deviation date; Figure 5 It is a framework diagram of a computer system. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0021] In the process of optimizing the dispatching of freight vehicles, there are great differences in the distribution of order users in different regions. Therefore, it is necessary to generate differentiated dispatching strategies based on the distribution of order users in different regions and the distribution of logistics orders, so as to reduce freight costs.

[0022] Freight demand coefficient of logistics delivery orders in a specified area: determine the total delivery volume of logistics delivery orders on different dates according to the delivery volumes of logistics delivery orders on different dates, determine the date on which the total delivery volume is greater than a preset delivery volume threshold according to the total delivery volume of logistics delivery orders on different dates, and use it as the delivery demand date, and determine the freight demand coefficient of the logistics delivery orders in the specified area based on the quantity ratio of the delivery demand date.

[0023] When the freight demand coefficient is between 0.5 and 0.8, it is determined that the freight demand coefficient is within the preset range.

[0024] Determine whether the changes in the delivery routes of the logistics delivery orders in the specified area meet the requirements: determine the overlapping data of the delivery routes of different logistics delivery orders based on the delivery routes of the logistics delivery orders in the specified area on different dates, determine the delivery routes with the most orders on different dates based on the overlapping data of the delivery routes of different logistics delivery orders, and use them as matching delivery routes, determine the deviation dates based on the deviations of the matching delivery routes between different dates and adjacent dates, and determine whether the changes in the delivery routes of the logistics delivery orders in the specified area meet the requirements based on the percentage of the number of deviation dates; Specifically, when the number of deviation dates accounts for more than 0.5, it is determined that the change in the delivery route of the logistics delivery orders in the specified area does not meet the requirements.

[0025] Freight Deviation Date: Determine the required number of freight vehicles on different dates based on the order data in adjacent areas and designated areas, and use the deviation between the allocated number of freight vehicles in adjacent areas and the required number to determine the date when freight vehicles do not meet the requirements.

[0026] Allocation strategy for freight vehicles in designated areas and adjacent areas: Determine the demand quantity of freight vehicles in designated areas and adjacent areas based on the freight demand coefficient of logistics distribution orders in designated areas and adjacent areas, and determine the allocation strategy for freight vehicles in designated areas and adjacent areas according to the demand quantity.

[0027] Embodiment 1 To solve the above problem, according to one aspect of the present invention, Figure 1 As shown, a first aspect is provided, and the present invention provides a logistics data analysis and processing method, which specifically includes: S1 determines the order data of the logistics delivery orders on different dates based on the acquired data of the logistics delivery orders on different dates in the designated area, and when the freight demand coefficient of the logistics delivery orders in the designated area is determined to be within a preset range based on the order data on different dates, proceeds to the next step; S2 determines the change of the delivery route of the logistics delivery order in the designated area based on the analysis results of the order data of different dates, and when the change of the delivery route of the logistics delivery order in the designated area meets the requirements, proceeds to the next step; S3 obtains the distribution data of freight vehicles in the adjacent areas of the designated area, and determines the date on which the freight vehicles do not meet the requirements based on the distribution data of the freight vehicles, the adjacent areas and the order data in the designated area, and uses the date as the freight deviation date; S4: When the deviation of freight vehicles on different freight deviation dates does not meet the requirements, the freight demand coefficient of the logistics delivery orders in the designated area and the adjacent areas is used to determine the allocation strategy of the freight vehicles in the designated area and the adjacent areas.

[0028] Furthermore, the acquisition data of the logistics delivery order is determined based on the order record data of the logistics delivery order of the logistics delivery platform.

[0029] Specifically, the order data of the logistics delivery order includes the delivery quantity of the logistics delivery order.

[0030] It should be noted that if Figure 2 As shown, the method for determining the freight demand coefficient of the logistics delivery order in the specified area is: Based on the order data of different dates, determine the delivery volume of the logistics delivery orders on different dates, and determine the total delivery volume of the logistics delivery orders on different dates according to the delivery volume of the logistics delivery orders on different dates; According to the total delivery volume of logistics delivery orders on different dates, determine the date when the total delivery volume is greater than the preset delivery volume threshold, and use it as the delivery demand date; The freight demand coefficient of the logistics delivery orders in the specified area is determined according to the quantity ratio of the delivery demand date.

[0031] Optionally, the freight demand coefficient of the logistics delivery orders in the designated area ranges from 0 to 1, wherein the larger the freight demand coefficient of the logistics delivery orders in the designated area, the higher the freight demand level of the logistics delivery orders in the designated area.

[0032] In another embodiment, when the freight demand coefficient of the logistics delivery orders in the designated area is not within a preset range, it is also necessary to determine whether the average of the total delivery volume of the logistics delivery orders on different dates is greater than the preset delivery volume. If so, it is determined that the designated area needs to be allocated freight vehicles. If not, it is determined that the designated area does not need to be allocated freight vehicles.

[0033] Optionally, the method for determining the freight demand coefficient of the logistics delivery order in the designated area is: Based on the order data of different dates, the delivery volume of the logistics delivery orders on different dates is determined, and according to the delivery volume of the logistics delivery orders on different dates and the order volume of the logistics delivery orders, the delivery demand coefficients on different dates are determined; Determine the delivery demand date based on the delivery demand coefficients of different dates; The freight demand coefficient of the logistics delivery orders in the specified area is determined according to the quantity ratio of the delivery demand date.

[0034] In one embodiment, the method for determining the freight demand coefficient of the logistics delivery order in the designated area is: S11 determines the delivery volume of the logistics delivery orders on different dates based on the order data on different dates, and determines the delivery demand coefficients on different dates according to the delivery volume of the logistics delivery orders on different dates and the order volume of the logistics delivery orders; Optionally, the above step S11 includes the following contents: S111 obtains the order quantity of logistics delivery orders on different dates based on the order data of different dates. When the order quantity of logistics delivery orders on different dates is less than the preset order quantity, it is determined that the freight demand coefficient of the logistics delivery orders in the specified area is not within the preset range. When there is a date when the order quantity of the logistics delivery orders is not less than the preset order quantity, the process proceeds to step S112. S112 determines the date when the total delivery amount is greater than the preset delivery amount based on the delivery amount of the logistics delivery orders on different dates, then proceeds to step S113. If there is no date when the total delivery amount is greater than the preset delivery amount, proceeds to step S114; S113: When the number of dates with a total delivery volume greater than the preset delivery volume is not within the preset date quantity interval, it is determined that the freight demand coefficient of the logistics delivery order in the specified area is not within the preset interval; when the number of dates with a total delivery volume greater than the preset delivery volume is within the preset date quantity interval, the process proceeds to step S114; S114 determines the delivery demand coefficients on different dates based on the delivery volumes of the logistics delivery orders on different dates and the order volumes of the logistics delivery orders. When the average value of the delivery demand coefficients on different dates is greater than the preset coefficient threshold, it is determined that the freight demand coefficient of the logistics delivery orders in the designated area is not within the preset range. When the average value of the delivery demand coefficients on different dates is not greater than the preset coefficient threshold, proceed to step S12.

[0035] S12 determines the delivery demand date according to the delivery demand coefficients of different dates; Optionally, the above step S12 includes the following contents: S121: When it is determined that there is no delivery demand date according to the delivery demand coefficients of different dates, it is determined that the freight demand coefficient of the logistics delivery order in the specified area is not within the preset range. When there is a delivery demand date, the process proceeds to step S122; S122 obtains the number of delivery demand dates. When the number of delivery demand dates is greater than the number of preset delivery dates, it is determined that the freight demand coefficient of the logistics delivery order in the specified area is not within the preset range. When the number of delivery demand dates is not greater than the number of preset delivery dates, the process proceeds to step S123; S123 obtains the number of delivery demand dates within the preset time period. When the number of delivery demand dates within the preset time period does not meet the requirement, it is determined that the designated area needs to be allocated freight vehicles. When the number of delivery demand dates within the preset time period meets the requirement, proceed to step S13.

[0036] S13 determines the freight demand coefficient of the logistics delivery orders in the designated area according to the delivery demand coefficients of different delivery demand dates and the quantity proportions of the delivery demand dates.

[0037] Furthermore, the change in the delivery route of the logistics delivery order is determined based on the change in the delivery route of the logistics delivery orders on different dates.

[0038] Specifically, Figure 3 As shown, determining whether the change of the delivery route of the logistics delivery order in the specified area meets the requirements specifically includes: Based on the order data of the logistics delivery orders in the designated area, the delivery routes of the logistics delivery orders in the designated area on different dates are determined, and according to the delivery routes of the logistics delivery orders in the designated area on different dates, the overlapping data of the delivery routes of different logistics delivery orders are determined; Based on the overlapping data of delivery routes of different logistics delivery orders, determine the matching delivery routes for different dates; Determine whether the change of the delivery route of the logistics delivery order in the designated area meets the requirements according to the deviation of the matching delivery routes between different dates.

[0039] Furthermore, the matching delivery route is the delivery route with the largest number of overlapping logistics delivery orders.

[0040] It should be noted that determining whether the change of the delivery route of the logistics delivery order in the designated area meets the requirements according to the deviation of the matching delivery routes between different dates specifically includes: Determine the deviation date based on the deviation of the matching delivery routes between different dates and adjacent dates; Whether the change in the delivery route of the logistics delivery order in the designated area meets the requirements is determined according to the quantity ratio of the deviation date.

[0041] Optionally, determining whether changes in delivery routes of logistics delivery orders in the designated area meet requirements specifically includes: S21 determines the delivery routes of the logistics delivery orders in the designated area on different dates based on the order data of the logistics delivery orders in the designated area, and determines the overlapping data of the delivery routes of different logistics delivery orders according to the delivery routes of the logistics delivery orders in the designated area on different dates; S22 determines the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates based on the overlapping data of the delivery routes of the different logistics delivery orders, and determines the comprehensive dispersion coefficient according to the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates; S23 determines matching delivery routes on different dates and corresponding logistics delivery orders of the matching delivery routes based on overlapping data of delivery routes of different logistics delivery orders, and determines a variation coefficient of the delivery routes of the logistics delivery orders based on the matching delivery routes on different dates and corresponding logistics delivery orders of the matching delivery routes; S24 determines the discrete evaluation quantity of the logistics delivery order in the specified area based on the comprehensive discrete coefficient and the variation coefficient of the delivery route of the logistics delivery order, and uses the discrete evaluation quantity to determine whether the variation of the delivery route meets the requirements.

[0042] Optionally, the above step S22 includes the following contents: S221 determines the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates based on the overlapping data of the delivery routes of the logistics delivery orders on different dates, obtains the average value of the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates, and when the average value of the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates does not meet the requirements, it is determined that the change of the delivery routes does not meet the requirements, and when the average value of the distribution dispersion coefficients of the delivery routes of the logistics delivery orders on different dates meets the requirements, proceeds to step S222; S222: When there is a date where the distribution dispersion coefficient does not meet the requirements, go to step S223; when there is no date where the distribution dispersion coefficient does not meet the requirements, go to step S224; S223 obtains the number of dates for which the distribution dispersion coefficient does not meet the requirements. When the number of dates for which the distribution dispersion coefficient does not meet the requirements is greater than the preset number of dates, it is determined that the change of the delivery route does not meet the requirements. When the number of dates for which the distribution dispersion coefficient does not meet the requirements is not greater than the preset number of dates, the process proceeds to step S224. S224 determines the comprehensive dispersion coefficient according to the distribution dispersion coefficient of the delivery routes of the logistics delivery orders on different dates. When the comprehensive dispersion coefficient does not meet the requirements, it is determined that the change of the delivery route does not meet the requirements. When the comprehensive dispersion coefficient meets the requirements, it goes to step S23.

[0043] Optionally, the above step S23 includes the following contents: S231 determines matching delivery routes for different dates based on the overlapping data of delivery routes for different logistics delivery orders, and determines the date quantity ratios corresponding to different matching delivery routes. When the date quantity ratios corresponding to different matching delivery routes are all less than the preset quantity ratios, it is determined that the change of the delivery route does not meet the requirements. When there is a matching delivery route whose date quantity ratio is not less than the preset quantity ratio, it proceeds to step S232. S232 determines the deviation date based on the deviation of the matching delivery routes between different dates and adjacent dates. When the number ratio of the deviation date is greater than the number ratio of the preset deviation date, it is determined that the change of the delivery route of the logistics delivery order in the specified area does not meet the requirements. When the number ratio of the deviation date is not greater than the number ratio of the preset deviation date, it proceeds to step S233. S233 determines the variation coefficient of the delivery route of the logistics delivery order based on the matching delivery routes of different dates and the corresponding logistics delivery orders of the matching delivery routes. When the variation coefficient of the delivery route of the logistics delivery order does not meet the requirement, it is determined that the variation of the delivery route of the logistics delivery order in the specified area does not meet the requirement. When the variation coefficient of the delivery route of the logistics delivery order meets the requirement, it proceeds to step S234. S234: When the coefficient of variation of the delivery route of the logistics delivery order is within the preset coefficient of variation range, the process proceeds to step S235; when the coefficient of variation of the delivery route of the logistics delivery order is not within the preset coefficient of variation range, the process proceeds to step S23; S235 When the comprehensive discrete coefficient is within the preset discrete coefficient range, it is determined that the change in the delivery route of the logistics delivery order in the designated area does not meet the requirements; when the comprehensive discrete coefficient is not within the preset discrete coefficient range, proceed to step S23.

[0044] Further, when the corresponding date quantities of different matching delivery routes are all less than the preset date quantity, it is determined that the change of the delivery routes of the logistics delivery orders in the designated area does not meet the requirements.

[0045] Specifically, the adjacent area is an area whose distance from the designated area is within a preset distance range.

[0046] It should be noted that the allocation data of the freight vehicles in the adjacent area includes the number of freight vehicles in the adjacent area.

[0047] Specifically, Figure 4 As shown, the method for determining the freight deviation date is: Determine the number of freight vehicles in different adjacent areas on the date based on the distribution data of the freight vehicles, and determine the total delivery volume of logistics delivery orders in the adjacent areas and the designated areas on the date based on the order data of the adjacent areas and the designated areas on the date; Determine the deviation number of freight vehicles on the date according to the total delivery volume of logistics delivery orders of the adjacent area and the designated area on the date and the number of freight vehicles in different adjacent areas on the date; It is determined whether the date is a freight deviation date based on the deviation number of freight vehicles on the date.

[0048] Furthermore, the method for determining the deviation number of freight vehicles on the date is: Determine the required number of freight vehicles for the total delivery volume according to the total delivery volume of logistics delivery orders of the adjacent area and the designated area on the date; The deviation quantity of the freight vehicles on the date is determined based on the demand quantity and the quantity of the freight vehicles.

[0049] Specifically, when the deviation number of freight vehicles on the date does not meet the requirement, it is determined that the date is a freight deviation date.

[0050] Optionally, the deviation of the freight vehicle for the freight deviation date does not meet the requirements, including: Determine the quantity ratio of freight deviation dates based on the deviation conditions of freight vehicles on different freight deviation dates, and determine the deviation proportional factor based on the quantity ratio of freight deviation dates; Obtaining deviation amounts of freight vehicles on different freight deviation dates, and determining a freight deviation coefficient using an average value of the deviation amounts of freight vehicles on different freight deviation dates; A comprehensive deviation coefficient is determined according to the deviation proportional factor and the freight deviation coefficient, and the comprehensive deviation coefficient is used to determine whether the deviation of the freight vehicle on the freight deviation date meets the requirements.

[0051] Furthermore, the freight deviation coefficient is determined according to the ratio of the average deviation amount of freight vehicles on different freight deviation dates to the number of freight vehicles in different adjacent areas.

[0052] It should be noted that when the comprehensive deviation coefficient is greater than the preset deviation coefficient threshold, it is determined that the deviation of the freight vehicle on the freight deviation date does not meet the requirements.

[0053] Optionally, when the deviation of the freight vehicles on the freight deviation date meets the requirements, there is no need to allocate freight vehicles in the designated area.

[0054] Specifically, the method for determining the allocation strategy of freight vehicles in the designated area and adjacent areas is: Determine the required number of freight vehicles in the designated area and adjacent areas based on the freight demand coefficient of logistics delivery orders in the designated area and adjacent areas; The allocation strategy of freight vehicles in the designated area and adjacent areas is determined according to the demand quantity.

[0055] Furthermore, the demand quantity of freight vehicles in the designated area is determined based on the product of the freight demand coefficient and a preset demand proportional factor. The matching quantity of freight vehicles is determined by the product of the specific freight demand coefficient and the preset demand proportional factor, and the matching quantity is used as the demand quantity of freight vehicles in the designated area.

[0056] Embodiment 2 In the second aspect, as Figure 5As shown, the present invention provides a computer system, comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned logistics data analysis and processing method when running the computer program.

[0057] In another embodiment, determining that the deviation of the freight vehicle on the freight deviation date does not meet the requirements specifically includes: Determine the number of freight deviation dates based on the deviation conditions of freight vehicles on different freight deviation dates, and when the number of freight deviation dates does not meet the requirement, determine that the deviation conditions of the freight vehicles on the freight deviation dates do not meet the requirement; When the quantity of the freight deviation date meets the requirement: Obtaining deviation amounts of freight vehicles on different freight deviation dates, taking freight deviation dates with deviation amounts greater than a preset deviation amount as screening deviation dates, and when the number of the screening deviation dates does not meet the requirement, determining that the deviation of the freight vehicles on the freight deviation date does not meet the requirement; When the number of screening deviation dates meets the requirement: Based on the number of the freight deviation dates and the ratio of the number of freight deviation dates, a basic deviation coefficient is determined. When the basic deviation coefficient does not meet the requirement, it is determined that the deviation of the freight vehicles on the freight deviation date does not meet the requirement; When the basic deviation coefficient meets the requirements: When the basic deviation coefficient is within the preset deviation coefficient range: Based on the deviation amounts of freight vehicles on different freight deviation dates, an average value of the deviation amounts of freight vehicles on different freight deviation dates is determined; when the average value of the deviation amounts of freight vehicles on different freight deviation dates is greater than a preset deviation amount threshold, it is determined that the deviation situation of the freight vehicle on the freight deviation date does not meet the requirement; When the basic deviation coefficient is not within the preset deviation coefficient range or the average deviation amount of freight vehicles on different freight deviation dates is not greater than the preset deviation amount threshold: Obtaining deviation amounts of freight vehicles on different freight deviation dates, and determining a freight deviation coefficient using an average value of the deviation amounts of freight vehicles on different freight deviation dates; A comprehensive deviation coefficient is determined according to the basic deviation coefficient and the freight deviation coefficient, and the comprehensive deviation coefficient is used to determine whether the deviation of the freight vehicle on the freight deviation date meets the requirements.

[0058] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0059] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0060] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A logistics data analysis and processing method, characterized in that: Specifically include: Based on the acquired data of logistics delivery orders on different dates in the designated area, order data of logistics delivery orders on different dates are determined, and when the freight demand coefficient of the logistics delivery orders in the designated area is determined to be within a preset range based on the order data on different dates, the next step is entered; Determine the change of the delivery route of the logistics delivery order in the designated area based on the analysis results of the order data of different dates, and proceed to the next step when the change of the delivery route of the logistics delivery order in the designated area meets the requirements; Obtaining the allocation data of freight vehicles in the adjacent areas of the designated area, and determining the date on which the freight vehicles do not meet the requirements based on the allocation data of the freight vehicles, the adjacent areas and the order data in the designated area, and using the date as the freight deviation date; When the deviation of freight vehicles on different freight deviation dates does not meet the requirements, the freight demand coefficients of the logistics delivery orders in the designated area and the adjacent areas are used to determine the allocation strategy of the freight vehicles in the designated area and the adjacent areas.

2. The logistics data analysis and processing method according to claim 1, characterized in that: The acquisition data of the logistics delivery order is determined according to the order record data of the logistics delivery order of the logistics delivery platform.

3. The logistics data analysis and processing method according to claim 1, characterized in that: The order data of the logistics delivery order includes the delivery quantity of the logistics delivery order.

4. The logistics data analysis and processing method according to claim 1, characterized in that: The method for determining the freight demand coefficient of the logistics delivery order in the specified area is: Based on the order data of different dates, determine the delivery volume of the logistics delivery orders on different dates, and determine the total delivery volume of the logistics delivery orders on different dates according to the delivery volume of the logistics delivery orders on different dates; According to the total delivery volume of logistics delivery orders on different dates, determine the date when the total delivery volume is greater than the preset delivery volume threshold, and use it as the delivery demand date; The freight demand coefficient of the logistics delivery orders in the specified area is determined according to the quantity ratio of the delivery demand date.

5. The logistics data analysis and processing method according to claim 4, characterized in that: The freight demand coefficient of the logistics delivery orders in the designated area ranges from 0 to 1, wherein the larger the freight demand coefficient of the logistics delivery orders in the designated area, the higher the freight demand level of the logistics delivery orders in the designated area.

6. The logistics data analysis and processing method according to claim 1, characterized in that: When the freight demand coefficient of the logistics delivery orders in the designated area is not within the preset range, it is also necessary to determine whether the average of the total delivery volume of the logistics delivery orders on different dates is greater than the preset delivery volume. If so, it is determined that freight vehicles need to be allocated to the designated area. If not, it is determined that freight vehicles do not need to be allocated to the designated area.

7. The logistics data analysis and processing method according to claim 1, characterized in that: The changes in the delivery routes of the logistics delivery orders are determined based on the changes in the delivery routes of the logistics delivery orders on different dates.

8. The logistics data analysis and processing method according to claim 1, characterized in that: The method for determining the allocation strategy of freight vehicles in the designated area and adjacent areas is: Determine the required number of freight vehicles in the designated area and adjacent areas based on the freight demand coefficient of logistics delivery orders in the designated area and adjacent areas; The allocation strategy of freight vehicles in the designated area and adjacent areas is determined according to the demand quantity.

9. The logistics data analysis and processing method according to claim 8, characterized in that: The demand quantity of freight vehicles in the designated area is determined based on the product of the freight demand coefficient and a preset demand proportional factor. The specific product of the freight demand coefficient and the preset demand proportional factor determines the matching quantity of freight vehicles, and the matching quantity is used as the demand quantity of freight vehicles in the designated area.

10. A computer system comprising: A memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes a logistics data analysis and processing method as described in any one of claims 1-9 when running the computer program.

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