CN112598337A - Article-oriented vehicle control method, apparatus, device and computer readable medium - Google Patents
Article-oriented vehicle control method, apparatus, device and computer readable medium Download PDFInfo
- Publication number
- CN112598337A CN112598337A CN202110227089.5A CN202110227089A CN112598337A CN 112598337 A CN112598337 A CN 112598337A CN 202110227089 A CN202110227089 A CN 202110227089A CN 112598337 A CN112598337 A CN 112598337A
- Authority
- CN
- China
- Prior art keywords
- historical
- target
- amount
- item
- item information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Data Mining & Analysis (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Development Economics (AREA)
- Evolutionary Computation (AREA)
- Educational Administration (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Traffic Control Systems (AREA)
Abstract
Embodiments of the present disclosure disclose a vehicle control method, apparatus, device and computer readable medium for an article. One embodiment of the method comprises: acquiring a historical article information set and target article information of an article; generating similarity between the historical item information and the target item information based on the historical circulation amount, the historical browsing amount, the historical circulation rate, the historical goods return rate and the target circulation amount, the target browsing amount, the target circulation rate and the target goods return rate which are included by each piece of historical item information in the historical item information set to obtain a similarity set; extracting historical item scheduling amount from historical item information corresponding to the similarity meeting the preset condition in the similarity set to obtain a historical item scheduling amount set; and controlling the associated vehicle to perform the item scheduling operation based on the historical item scheduling amount set. This embodiment reduces the number of times that the number of articles scheduled cannot meet the user's needs, reducing the loss of user traffic.
Description
Technical Field
Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a computer-readable medium for controlling a vehicle for an article.
Background
With the development of internet technology and electronic commerce, the number of items ordered by a user through an e-commerce platform shows a sudden increase trend, and related vehicles need to be controlled to schedule the items so as to meet the requirements of the user. At present, when dispatching articles, the general adopted method is as follows: firstly, determining the adjustment amount of an article according to expert experience knowledge; and then controlling the relevant vehicle to dispatch the item according to the determined dispatching quantity.
However, when the above-mentioned manner is adopted to schedule the articles, the following technical problems often exist:
firstly, the determined scheduling amount is subjective, so that the number of times that the number of the scheduled articles cannot meet the user requirement is large, the delivery timeliness is poor, the user experience is poor, and the flow of the user is lost.
Secondly, the influence of the commodity circulation amount, the browsing amount, the circulation rate and the goods return rate on the dispatching amount is not considered, so that the dispatching amount is low in accuracy, the number of times that the quantity of dispatched commodities cannot meet the requirements of users is large, the delivery timeliness is poor, the user experience is poor, and the user flow loss is caused.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose vehicle control methods, apparatuses, devices and computer readable media for articles to solve one or more of the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide a method of vehicle control for an article, the method comprising: acquiring a historical article information set and target article information of an article, wherein the historical article information in the historical article information set comprises a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical goods return rate and a historical article dispatching amount, and the target article information comprises a target circulation amount, a target browsing amount, a target circulation rate and a target goods return rate; generating similarity between the historical item information and the target item information based on the historical circulation amount, the historical browsing amount, the historical circulation rate and the historical return rate included by each piece of historical item information in the historical item information set, and the target circulation amount, the target browsing amount, the target circulation rate and the target return rate, so as to obtain a similarity set; in response to the similarity meeting the preset condition existing in the similarity set, extracting historical item scheduling quantity from historical item information corresponding to the similarity meeting the preset condition in the similarity set to obtain a historical item scheduling quantity set; and controlling the associated vehicle to execute the item scheduling operation based on the historical item scheduling amount set.
In some embodiments, the generating the similarity between the historical item information and the target item information includes:
generating the similarity between the historical item information and the target item information by the following formula:
wherein the content of the first and second substances,
the historical item information is represented by a representation of,
the information of the target item is represented,
representing the historical item information
And the target article information
The degree of similarity of (a) to (b),
representing the normalized historical amount of streaming,
represents the normalized historical browsing volume,
representing the historical flow-through rate of the flow,
indicating the historical rate of return of goods,
represents the normalized target amount of flow,
represents the normalized target browsing volume,
represents the target flow-through rate and,
the target return rate is represented by a value representing the target return rate,
to represent
And
the absolute value of the difference of (a) is,
to represent
And
the absolute value of the difference of (a).
In a second aspect, some embodiments of the present disclosure provide a vehicle control apparatus for an article, the apparatus comprising: the system comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is configured to acquire a historical item information set and target item information of an item, the historical item information in the historical item information set comprises a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical return rate and a historical item transfer amount, and the target item information comprises a target circulation amount, a target browsing amount, a target circulation rate and a target return rate; a generating unit configured to generate a similarity between the historical item information and the target item information based on a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical return rate, and the target circulation amount, the target browsing amount, the target circulation rate, and the target return rate included in each piece of historical item information in the historical item information set, so as to obtain a similarity set; an extracting unit, configured to, in response to a similarity meeting a predetermined condition existing in the similarity set, extract a historical item scheduling amount from historical item information corresponding to the similarity meeting the predetermined condition in the similarity set, so as to obtain a historical item scheduling amount set; and the control unit is configured to control the associated vehicle to execute the item scheduling operation based on the historical item scheduling amount set.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.
In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.
The above embodiments of the present disclosure have the following advantages: with the article-specific vehicle control method of some embodiments of the present disclosure, user traffic loss is reduced. Specifically, the reason for the loss of user traffic is: the determined dispatching amount is subjective, so that the number of times that the quantity of dispatched articles cannot meet the requirements of users is large, the delivery timeliness is poor, and the user experience is poor. Based on this, the vehicle control method for an article of some embodiments of the present disclosure first acquires a historical article information set and target article information of the article. The historical item information in the historical item information set comprises historical circulation amount, historical browsing amount, historical circulation rate, historical return rate and historical item adjustment amount. The target article information comprises a target circulation amount, a target browsing amount, a target circulation rate and a target return rate. Therefore, the historical flow amount, the historical browsing amount, the historical flow rate, the historical return rate and the historical item adjustment amount included in the acquired historical item information and the target flow amount, the target browsing amount, the target flow rate and the target return rate included in the target item information can provide support for generating the similarity of the historical item information and the target item information. Then, based on the historical circulation amount, the historical browsing amount, the historical circulation rate and the historical return rate included in each piece of historical article information in the historical article information set, and the target circulation amount, the target browsing amount, the target circulation rate and the target return rate, the similarity between the historical article information and the target article information is generated, and a similarity set is obtained. Thus, the degree of similarity between the historical item information and the target item information can be quantitatively expressed by the historical flow amount, the historical browsing amount, the historical flow rate, the historical return rate and the historical item adjustment amount included in the historical item information and the target flow amount, the target browsing amount, the target flow rate and the target return rate included in the target item information. And then, in response to the similarity meeting the preset condition in the similarity set, extracting the historical item scheduling amount from the historical item information corresponding to the similarity meeting the preset condition in the similarity set to obtain a historical item scheduling amount set. Therefore, the extracted historical item scheduling amount set can provide support for item scheduling. And finally, controlling the associated vehicle to execute the item scheduling operation based on the historical item scheduling amount set. Therefore, the related vehicles can be controlled to carry out article scheduling according to the objective historical article scheduling amount set. And because the similarity between the historical item information and the target item information is quantified, a more objective historical item scheduling amount set can be obtained. Therefore, a relatively objective dispatching amount can be determined according to the objective historical item dispatching amount set, the number of times that the quantity of dispatched items cannot meet the user requirement can be reduced, the delivery timeliness is improved, and the user experience is improved. And further reduces the loss of user traffic.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.
FIG. 1 is a schematic diagram of one application scenario of a vehicle control method for an article, according to some embodiments of the present disclosure;
FIG. 2 is a flow chart of some embodiments of a vehicle control method for an article according to the present disclosure;
FIG. 3 is a flow chart of further embodiments of a vehicle control method for an article according to the present disclosure;
FIG. 4 is a schematic block diagram of some embodiments of a vehicle control apparatus for an article according to the present disclosure;
FIG. 5 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a schematic diagram of one application scenario of a vehicle control method for an article according to some embodiments of the present disclosure.
In the application scenario of fig. 1, first, the computing device 101 may obtain a set of historical item information 102 and target item information 103 for an item. The historical item information in the historical item information set 102 includes historical flow amount, historical browsing amount, historical flow rate, historical return rate, and historical item adjustment amount. The target item information 103 includes a target amount of circulation 1031, a target amount of browsing 1032, a target rate of circulation 1033, and a target rate of return 1034. Then, the computing device 101 may generate similarity between the historical item information and the target item information 103 based on the historical flow amount, the historical browsing amount, the historical flow rate, and the historical return rate included in each historical item information in the historical item information set 102, and the target flow amount 1031, the target browsing amount 1032, the target flow rate 1033, and the target return rate 1034, to obtain a similarity set 104. Then, in response to the similarity meeting the predetermined condition existing in the similarity set 104, the computing device 101 may extract a historical item scheduling amount from historical item information corresponding to the similarity meeting the predetermined condition in the similarity set 104, so as to obtain a historical item scheduling amount set 105. Finally, the computing device 101 may control the associated vehicle 106 to perform an item scheduling operation based on the set 105 of historical item scheduling amounts.
The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.
With continued reference to fig. 2, a flow 200 of some embodiments of a vehicle control method for an article according to the present disclosure is shown. The article-oriented vehicle control method comprises the following steps:
In some embodiments, an executing subject (e.g., the computing device 101 shown in fig. 1) of the vehicle control method for an item may acquire the historical item information set and the target item information of the item from a terminal by a wired connection manner or a wireless connection manner. The historical item information in the historical item information set may include historical flow amount, historical browsing amount, historical flow rate, historical return rate, and historical item adjustment amount. Each historical item information in the historical item information set corresponds to a preset first historical time period. The historical diversion amount may be a diversion amount (e.g., sales) of the item over a corresponding predetermined first historical time period. The historical browsing volume may be a browsing volume of the detail page of the item within the predetermined first historical time period. The historical streaming rate may be a ratio of the historical streaming amount to the historical browsing amount. The historical return rate may be a ratio of the return volume of the item to the historical diversion volume over the predetermined first historical time period. The historical item scheduling amount may be the number of the items scheduled in the predetermined first historical time period. The target item information may include a target amount of circulation, a target browsing amount, a target circulation rate, and a target return rate. The target item information may be related information of the item within a predetermined second historical time period. The predetermined second history period may be a history period after the predetermined first history period. The time interval of the predetermined second history time period is equal to the first history time period. Here, the setting of the predetermined first history time period and the predetermined second history time period is not limited. The target amount of runoff may be an amount of runoff (e.g., sales) of the item over a predetermined second historical period of time. The target browsing volume may be a browsing volume of the detail page of the item in the predetermined second history time period. The target streaming rate may be a ratio of the target streaming amount to the target browsing amount. The target return rate may be a ratio of a return amount of the article to the target diversion amount during the predetermined second historical time period. It should be noted that the wireless connection means may include, but is not limited to, a 3G/4G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, a uwb (ultra wideband) connection, and other wireless connection means now known or developed in the future. Therefore, the historical flow amount, the historical browsing amount, the historical flow rate, the historical return rate and the historical item adjustment amount included in the acquired historical item information and the target flow amount, the target browsing amount, the target flow rate and the target return rate included in the target item information can provide support for generating the similarity of the historical item information and the target item information.
As an example, the historical item information set for item "001" may be:
"[ historical traffic: 20, historical browsing volume: 100, historical turnover: 0.2, historical return rate: 0.1, historical item adjustment amount: 6],
[ historical traffic volume: 21, historical browsing volume: 100, historical turnover: 0.21, historical return rate: 0.05, historical item adjustment amount: 6],
[ historical traffic volume: 50, historical browsing volume: 100, historical turnover: 0.5, historical return rate: 0, historical item adjustment amount: 10]". The "001" may be an identification of the article. In the historical item information set, the predetermined first historical time period corresponding to the first historical item information may be "2021/1/112: 00-2021/1/712: 00". The predetermined first historical time period corresponding to the second historical item information may be "2021/1/712: 00-2021/1/1412: 00". The predetermined first historical time period corresponding to the third historical item information may be "2021/1/1412: 00-2021/1/2112: 00". The target article information may be [ target amount of circulation: 19, target browsing volume: 100, target turnover: 0.19, target return rate: 0.05]. The predetermined second history time period corresponding to the above target item information may be "2021/1/2112: 00-2021/1/2812: 00".
In some embodiments, the execution subject may generate a similarity between the historical item information and the target item information based on a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical return rate, the target circulation amount, the target browsing amount, the target circulation rate, and the target return rate included in each historical item information in the historical item information set, to obtain a similarity set. In practice, the executing entity may generate the similarity between the historical item information and the target item information according to the following formula:
wherein the content of the first and second substances,
the historical item information is displayed.
The target item information is represented.
Indicating the historical article information
And the target article information
The similarity of (c).
Representing the historical traffic described above.
Indicating the above-mentioned historical browsing volume.
Representing the historical slew rate.
Representing the historical return rate.
Indicating the target amount of flow.
The target browsing amount is represented.
Representing the target streaming rate.
Representing the target return rate. Thus, the degree of similarity between the historical item information and the target item information can be quantitatively expressed by the historical flow amount, the historical browsing amount, the historical flow rate, the historical return rate and the historical item adjustment amount included in the historical item information and the target flow amount, the target browsing amount, the target flow rate and the target return rate included in the target item information.
As an example, the above-mentioned historical item information
The historical item information [ historical traffic volume: 20, historical browsing volume: 100, historical turnover: 0.2, historical return rate: 0.1, historical item adjustment amount: 6]. The target article information
Target item information [ target amount of flow: 19, target browsing volume: 100, target turnover: 0.19, target return rate: 0.05]. Then
Is 20.
Is 100.
Is 0.2.
Is 0.1.
Is 19.
Is 100.
Is 0.19.
Is 0.05. The execution agent may generate the historical item information by the formula
And the target article information
Degree of similarity of
. Thus, a similarity set [0.999345, 0.999902, 0.978048] can be obtained]. Here, the numerical value of the above-described similarity may be retained to six digits after the decimal point.
In some embodiments, the execution subject may extract, in response to the similarity meeting the predetermined condition existing in the similarity set, a historical item scheduling amount from historical item information corresponding to the similarity meeting the predetermined condition in the similarity set, so as to obtain a historical item scheduling amount set. The predetermined condition may be "similarity is equal to or greater than a predetermined threshold". Here, the setting of the predetermined threshold is not limited. In practice, first, the execution subject may determine whether there is a similarity satisfying the predetermined condition in the similarity set. Then, in response to the determination, the similarity satisfying the predetermined condition in the similarity set may be determined as a target similarity, resulting in a target similarity set. Then, historical item information corresponding to each target similarity in the target similarity set in the historical item information set may be determined as target historical item information, and a target historical item information set may be obtained. Finally, historical item scheduling amounts can be extracted from all target historical item information in the target historical item information set, and a historical item scheduling amount set is obtained. Therefore, the extracted historical item scheduling amount set can provide support for item scheduling.
As an example, the predetermined threshold may be 0.98. The predetermined condition may be "similarity is 0.98 or more". The similarity set may be [0.999345, 0.999902, 0.978048 ]. First, the execution subject may determine that there is a similarity satisfying the predetermined condition in the similarity set. Then, the similarity satisfying the predetermined condition "similarity is 0.98 or more" in the similarity set may be determined as a target similarity, resulting in a target similarity set [0.999345, 0.999902 ]. Then, historical item information corresponding to each target similarity in the target similarity set [0.999345, 0.999902] in the historical item information set may be determined as target historical item information, and a target historical item information set "[ historical traffic: 20, historical browsing volume: 100, historical turnover: 0.2, historical return rate: 0.1, historical item adjustment amount: 6], [ historical traffic: 21, historical browsing volume: 100, historical turnover: 0.21, historical return rate: 0.05, historical item adjustment amount: 6]". Finally, historical item scheduling amounts can be extracted from each target historical item information of the target historical item information set to obtain a historical item scheduling amount set [6, 6 ].
And step 204, controlling the associated vehicle to execute the item scheduling operation based on the historical item scheduling amount set.
In some embodiments, the execution subject may control the associated vehicle to perform the item scheduling operation based on the set of historical item scheduling amounts. In practice, the executing subject may first determine a mean value of the historical item allocation amounts in the historical item allocation amount set as a target allocation amount. Then, the vehicle may be controlled to perform an item scheduling operation according to the target scheduling amount. For example, the vehicle may be controlled to dispatch the target dispatch amount of the item. Therefore, the related vehicles can be controlled to carry out article scheduling according to the objective historical article scheduling amount set.
Optionally, the executing entity may execute, in response to that there is no similarity satisfying the predetermined condition in the similarity set, the following steps:
the first step is to generate a target historical item adjustment amount based on each historical item adjustment amount included in the historical item information set. In practice, the execution subject may determine a maximum value among the respective historical item allocation amounts as a target historical item allocation amount.
In some optional implementations of some embodiments, the performing subject may determine an average of the respective historical item allocation amounts as a target historical item allocation amount.
And secondly, controlling the associated vehicle to execute the item scheduling operation based on the target historical item scheduling amount. In practice, the execution body may control the vehicle to execute the article scheduling operation according to the target historical article scheduling amount. For example, the vehicle may be controlled to dispatch the target historical item dispatch amount of the item.
Thus, the associated vehicle can be controlled to perform the article scheduling operation in the case where there is no similarity satisfying the predetermined condition in the similarity set.
Alternatively, first, the execution subject may generate item scheduling display information based on the historical item scheduling amount set. In practice, the execution subject may determine a maximum value of each historical item scheduling amount in the historical item scheduling amount set as item scheduling display information. As an example, the set of historical item quantities may be [6, 6 ]. The execution body may determine a maximum value [6] of each historical item scheduling amount in the historical item scheduling amount set as item scheduling display information.
In some optional implementations of some embodiments, the executing entity may determine, as the item scheduling display information, an average of respective historical item scheduling amounts in the set of historical item scheduling amounts. As an example, the set of historical item quantities may be [6, 6 ]. The execution subject may determine an average [6] of the respective historical item scheduling amounts in the historical item scheduling amount set as item scheduling display information.
The item scheduling display information may then be transmitted to a display device associated with the vehicle for the display device to display the item scheduling display information. In practice, the execution main body may send the article scheduling display information to a display device associated with the vehicle through a wired connection manner or a wireless connection manner, so that the display device displays the article scheduling display information.
Thus, the display device associated with the vehicle can be caused to display the item scheduling display information.
The above embodiments of the present disclosure have the following advantages: with the article-specific vehicle control method of some embodiments of the present disclosure, user traffic loss is reduced. Specifically, the reason for the loss of user traffic is: the determined dispatching amount is subjective, so that the number of times that the quantity of dispatched articles cannot meet the requirements of users is large, the delivery timeliness is poor, and the user experience is poor. Based on this, the vehicle control method for an article of some embodiments of the present disclosure first obtains a historical article information set of the article, where historical article information in the historical article information set includes a historical amount of circulation, a historical browsing amount, a historical circulation rate, a historical return rate, and a historical article adjustment amount, and target article information including a target amount of circulation, a target browsing amount, a target circulation rate, and a target return rate. Therefore, the historical flow amount, the historical browsing amount, the historical flow rate, the historical return rate and the historical item adjustment amount included in the acquired historical item information and the target flow amount, the target browsing amount, the target flow rate and the target return rate included in the target item information can provide support for generating the similarity of the historical item information and the target item information. Then, based on the historical circulation amount, the historical browsing amount, the historical circulation rate and the historical return rate included in each piece of historical article information in the historical article information set, and the target circulation amount, the target browsing amount, the target circulation rate and the target return rate, the similarity between the historical article information and the target article information is generated, and a similarity set is obtained. Thus, the degree of similarity between the historical item information and the target item information can be quantitatively expressed by the historical flow amount, the historical browsing amount, the historical flow rate, the historical return rate and the historical item adjustment amount included in the historical item information and the target flow amount, the target browsing amount, the target flow rate and the target return rate included in the target item information. And then, in response to the similarity meeting the preset condition in the similarity set, extracting the historical item scheduling amount from the historical item information corresponding to the similarity meeting the preset condition in the similarity set to obtain a historical item scheduling amount set. Therefore, the extracted historical item scheduling amount set can provide support for item scheduling. And finally, controlling the associated vehicle to execute the item scheduling operation based on the historical item scheduling amount set. Therefore, the related vehicles can be controlled to carry out article scheduling according to the objective historical article scheduling amount set. And because the similarity between the historical item information and the target item information is quantified, a more objective historical item scheduling amount set can be obtained. Therefore, a relatively objective dispatching amount can be determined according to the objective historical item dispatching amount set, the number of times that the quantity of dispatched items cannot meet the user requirement can be reduced, the delivery timeliness is improved, and the user experience is improved. And further reduces the loss of user traffic.
With further reference to FIG. 3, a flow 300 of further embodiments of a vehicle control method for an article is shown. The flow 300 of the article-specific vehicle control method includes the following steps:
In some embodiments, the specific implementation of step 301 and the technical effect brought by the implementation may refer to step 201 in those embodiments corresponding to fig. 2, and are not described herein again.
In some embodiments, an executing subject (e.g., the computing device 101 shown in fig. 1) of the article-specific vehicle control method may perform normalization processing on the target traffic flow based on each historical traffic flow included in the historical article information set, so as to obtain a normalized target traffic flow. In practice, the execution body may perform normalization processing on the target traffic flow based on the historical traffic flow and the target traffic flow through a Min-Max normalization formula to obtain a normalized target traffic flow. Thus, the target traffic volume can be mapped in the range of [0, 1], and support can be provided for unifying the dimensions of data of each dimension when generating the similarity.
As an example, the target amount of the flow may be the target amount of flow [19 ] in the example of step 201]. The minimum value of each historical flow amount and the target flow amount included in the historical item information set illustrated in step 201 is 19. The maximum value of the historical traffic and the target traffic included in the historical item information set illustrated in step 201 is 50. The execution body can execute the target flow amount [19 ]]Carrying out normalization processing to obtain a normalized target flow rate
。
In some embodiments, the execution subject may perform normalization processing on the target browsing volume based on each historical browsing volume included in the historical item information set, so as to obtain a normalized target browsing volume. In practice, the execution subject may perform normalization processing on the target browsing volume based on the historical browsing volumes and the target browsing volume through a Min-Max standardized formula to obtain a normalized target browsing volume. Therefore, the target browsing amount can be mapped in the range of [0, 1], and support can be provided for unifying the dimension of the data of each dimension when generating the similarity.
As an example, the target browsing amount may be the target browsing amount [100 ] in the example of step 201]. The minimum value and the maximum value of each historical browsing volume and the target browsing volume included in the historical item information set illustrated in step 201 are both 100. The execution subject can browse the target amount [100 ]]Carrying out normalization processing to obtain normalized target browsing volume
。
And 304, normalizing the historical traffic based on each historical traffic and the target traffic included in the historical item information set to obtain normalized historical traffic.
In some embodiments, the execution body may perform normalization processing on the historical traffic based on each historical traffic included in the historical item information set and the target traffic, so as to obtain a normalized historical traffic. In practice, the execution body may normalize the historical traffic based on the historical traffic and the target traffic through a Min-Max normalization formula to obtain a normalized historical traffic. Therefore, the historical traffic can be mapped in the range of [0, 1], and support can be provided for unifying the dimension of the data of each dimension when generating the similarity.
As an example, the historical item information may be the historical item information in the historical item information set illustrated in step 201Information [ historical traffic: 20, historical browsing volume: 100, historical turnover: 0.2, historical return rate: 0.1, historical item adjustment amount: 6]. The above historical traffic is [20 ]]. The target amount of the flow may be the target amount of the flow [19 ] in the example of step 201]. The minimum value of each historical flow amount and the target flow amount included in the historical item information set illustrated in step 201 is 19. The maximum value of the historical traffic and the target traffic included in the historical item information set illustrated in step 201 is 50. The execution body may be for historical traffic [20 ]]Carrying out normalization processing to obtain normalized historical traffic
。
And 305, normalizing the historical browsing amount based on each historical browsing amount and target browsing amount included in the historical item information set to obtain a normalized historical browsing amount.
In some embodiments, the execution subject may perform normalization processing on the historical browsing amount based on each historical browsing amount and the target browsing amount included in the historical item information set, so as to obtain a normalized historical browsing amount. In practice, the execution subject may perform normalization processing on the historical browsing volumes based on the historical browsing volumes and the target browsing volume by using a Min-Max standardized formula to obtain a normalized historical browsing volume. Therefore, the historical browsing amount can be mapped in the range of [0, 1], and support can be provided for unifying the dimension of the data of each dimension when generating the similarity.
As an example, the historical item information may be historical item information [ historical traffic volume: 20, historical browsing volume: 100, historical turnover: 0.2, historical return rate: 0.1, historical item adjustment amount: 6]. The above-mentioned historical browsing amount is [100 ]]. The target browsing volume may be the target browsing volume [100 ] in the example of step 201]. The minimum value and the maximum value of each historical browsing volume and the target browsing volume included in the historical item information set illustrated in step 201 are both 100. As described aboveThe execution subject may view the historical view volume 100]Carrying out normalization processing to obtain normalized historical browsing amount
。
And step 306, generating the similarity between the historical item information and the target item information based on the normalized historical circulation amount, the normalized historical browsing amount, the normalized historical circulation rate, the historical goods return rate, the normalized target circulation amount, the normalized target browsing amount, the target circulation rate and the target goods return rate.
In some embodiments, the execution body may generate the similarity between the historical item information and the target item information in various ways based on the normalized historical diversion amount, the normalized historical browsing amount, the historical diversion rate, the historical return rate, the normalized target diversion amount, the normalized target browsing amount, the target diversion rate, and the target return rate.
In some optional implementations of some embodiments, the executing entity may generate a similarity between the historical item information and the target item information by the following formula:
wherein the content of the first and second substances,
the historical item information is displayed.
The target item information is represented.
Indicating the historical article information
And the target article information
The similarity of (c).
Representing the normalized historical traffic described above.
Representing the normalized historical browsing volume.
Representing the historical slew rate described above.
Representing the historical return rate.
Representing the normalized target traffic as described above.
Representing the normalized target browsing volume.
Indicating the target slew rate.
Indicating the target return rate.
To represent
And
the absolute value of the difference of (a).
To represent
And
the absolute value of the difference of (a).
As an example, the above-mentioned historical item information
The historical item information [ historical traffic volume: 20, historical browsing volume: 100, historical turnover: 0.2, historical return rate: 0.1, historical item adjustment amount: 6]. The target article information
The target item information [ target amount of circulation: 19, target browsing volume: 100, target turnover: 0.19, target return rate: 0.05]。
May be exemplified by step 304
。
May be 1 of the example of step 305.
Is 0.2.
Is 0.1.
May be 0 as illustrated in step 302.
May be 1 as illustrated in step 304.
Is 0.19.
Is 0.05. The execution agent may generate the historical item information by the formula
And the target article information
Degree of similarity of
. Here, the numerical value of the similarity may be retained to two digits after the decimal point.
The above formula and its related content are used as an invention point of the embodiment of the disclosure, and solve the technical problems mentioned in the background art that the influence of the commodity circulation amount, browsing amount, circulation rate and return rate on the dispatching amount is not considered, so that the dispatching amount is low in accuracy, the number of dispatched commodities is large in times that the quantity of dispatched commodities cannot meet the user requirement, the dispatching timeliness is poor, the user experience is poor, and the user traffic is lost. The factors that cause the loss of user traffic are often as follows: the influence of the logistics amount, the browsing amount, the logistics rate and the return rate of the articles on the dispatching amount is not considered, so that the dispatching amount is low in accuracy, the number of times that the quantity of dispatched articles cannot meet the requirements of users is large, the delivery timeliness is poor, and the user experience is poor. If the above factors are solved, the effect of reducing the user flow loss can be achieved. To achieve this effect, the present disclosure introduces a historical amount of circulation, a historical browsing amount, a historical circulation rate, and a historical return rate included in the historical item information, and a target amount of circulation, a target browsing amount, a target circulation rate, and a target return rate included in the target item information. The similarity between the historical article information and the target article information can be determined by normalizing the historical circulation amount and the normalized target circulation amount, normalizing the historical browsing amount and the normalized target browsing amount, the historical circulation rate and the target circulation rate, and the historical goods return rate and the target goods return rate. And the formula is determined by the distance, the historical item information can be selected to extract the historical item scheduling amount through the similarity between each piece of historical item information and the target item information, and therefore the scheduling operation of the associated vehicle can be controlled according to each extracted historical item scheduling amount. Therefore, the influence of the commodity circulation amount, the browsing amount, the circulation rate and the goods return rate on the dispatching amount is comprehensively considered, and the accuracy of the dispatching amount is improved. Therefore, the times that the number of dispatched articles cannot meet the requirements of users are reduced, and the delivery timeliness and the user experience are improved. Thereby reducing the loss of user traffic.
And step 308, controlling the associated vehicle to execute the item scheduling operation based on the historical item scheduling amount set.
In some embodiments, the specific implementation and technical effects of steps 307-308 may refer to steps 203-204 in those embodiments corresponding to fig. 2, which are not described herein again.
As can be seen from fig. 3, compared with the description of some embodiments corresponding to fig. 2, the flow 300 of the article-specific vehicle control method in some embodiments corresponding to fig. 3 embodies the step of expanding the similarity between the generated historical article information and the target article information. Therefore, the scheme described in the embodiments can comprehensively consider the influence of the article flow rate, the browsing amount, the flow rate and the return rate on the adjusting amount, and improve the accuracy of the adjusting amount. Therefore, the times that the number of dispatched articles cannot meet the requirements of users can be reduced, and the delivery timeliness and the user experience can be improved. Thereby reducing the loss of user traffic.
With further reference to fig. 4, as an implementation of the methods illustrated in the above figures, the present disclosure provides some embodiments of a vehicle control apparatus for an article, which correspond to those method embodiments illustrated in fig. 2, which may be particularly applicable in various electronic devices.
As shown in fig. 4, the article-directed vehicle control apparatus 400 of some embodiments includes: an acquisition unit 401, a generation unit 402, an extraction unit 403, and a control unit 404. The obtaining unit 401 is configured to obtain a historical item information set and target item information of an item, where the historical item information in the historical item information set includes a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical return rate and a historical item adjustment amount, and the target item information includes a target circulation amount, a target browsing amount, a target circulation rate and a target return rate; the generating unit 402 is configured to generate a similarity between the historical item information and the target item information based on a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical return rate, and the target circulation amount, the target browsing amount, the target circulation rate, and the target return rate included in each piece of historical item information in the historical item information set, so as to obtain a similarity set; the extracting unit 403 is configured to, in response to a similarity meeting a predetermined condition existing in the similarity set, extract a historical item scheduling amount from historical item information corresponding to the similarity meeting the predetermined condition in the similarity set, so as to obtain a historical item scheduling amount set; the control unit 404 is configured to control the associated vehicle to perform an item scheduling operation based on the set of historical item scheduling amounts.
In an optional implementation of some embodiments, the article-directed vehicle control apparatus 400 may further include: an execution unit configured to, in response to no similarity satisfying the predetermined condition existing in the similarity set, execute the following steps: generating a target historical item adjustment amount based on each historical item adjustment amount included in the historical item information set; and controlling the associated vehicle to execute the item scheduling operation based on the target historical item scheduling amount.
It will be understood that the elements described in the apparatus 400 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 400 and the units included therein, and will not be described herein again.
Referring now to FIG. 5, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1) 500 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 5 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a historical article information set and target article information of an article, wherein the historical article information in the historical article information set comprises a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical goods return rate and a historical article dispatching amount, and the target article information comprises a target circulation amount, a target browsing amount, a target circulation rate and a target goods return rate; generating similarity between the historical item information and the target item information based on the historical circulation amount, the historical browsing amount, the historical circulation rate and the historical return rate included by each piece of historical item information in the historical item information set, and the target circulation amount, the target browsing amount, the target circulation rate and the target return rate, so as to obtain a similarity set; in response to the similarity meeting the preset condition existing in the similarity set, extracting historical item scheduling quantity from historical item information corresponding to the similarity meeting the preset condition in the similarity set to obtain a historical item scheduling quantity set; and controlling the associated vehicle to execute the item scheduling operation based on the historical item scheduling amount set.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a generation unit, an extraction unit, and a control unit. Where the names of these units do not in some cases constitute a limitation on the units themselves, for example, the control unit may also be described as a "unit that controls the associated vehicle to perform an item scheduling operation based on the above-described set of historical item scheduling amounts".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (10)
1. A vehicle control method for an article, comprising:
acquiring a historical article information set and target article information of an article, wherein the historical article information in the historical article information set comprises a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical goods return rate and a historical article adjusting amount, and the target article information comprises a target circulation amount, a target browsing amount, a target circulation rate and a target goods return rate;
generating similarity between the historical item information and the target item information based on the historical circulation amount, the historical browsing amount, the historical circulation rate and the historical goods return rate included by each piece of historical item information in the historical item information set, and the target circulation amount, the target browsing amount, the target circulation rate and the target goods return rate, so as to obtain a similarity set;
in response to the similarity meeting a preset condition in the similarity set, extracting historical item scheduling quantity from historical item information corresponding to the similarity meeting the preset condition in the similarity set to obtain a historical item scheduling quantity set;
and controlling the associated vehicle to perform an item scheduling operation based on the set of historical item scheduling amounts.
2. The method of claim 1, wherein the method further comprises:
in response to there being no similarity in the set of similarities that satisfies the predetermined condition, performing the following steps:
generating a target historical item allocation amount based on each historical item allocation amount included in the historical item information set;
controlling the associated vehicle to perform an item scheduling operation based on the target historical item scheduling amount.
3. The method of claim 2, wherein the generating a target historical item allocation amount comprises:
and determining the average value of the historical item adjustment quantities as a target historical item adjustment quantity.
4. The method of claim 1, wherein the method further comprises:
generating item scheduling display information based on the historical item scheduling amount set;
and sending the article scheduling display information to display equipment associated with the vehicle so that the display equipment can display the article scheduling display information.
5. The method of claim 4, wherein the generating item scheduling display information comprises:
and determining the average value of all historical item scheduling amounts in the historical item scheduling amount set as item scheduling display information.
6. The method according to claim 1, wherein the generating the similarity of the historical item information and the target item information based on the historical circulation amount, the historical browsing amount, the historical circulation rate and the historical return rate of each historical item information in the historical item information set and the target circulation amount, the target browsing amount, the target circulation rate and the target return rate, and obtaining a similarity set comprises:
based on each historical traffic amount included in the historical item information set, carrying out normalization processing on the target traffic amount to obtain a normalized target traffic amount;
and based on each historical browsing amount included in the historical item information set, carrying out normalization processing on the target browsing amount to obtain a normalized target browsing amount.
7. The method of claim 6, wherein the generating a similarity of the historical item information and the target item information comprises:
based on each historical traffic and the target traffic included in the historical item information set, carrying out normalization processing on the historical traffic to obtain normalized historical traffic;
based on each historical browsing amount and the target browsing amount included in the historical item information set, carrying out normalization processing on the historical browsing amount to obtain a normalized historical browsing amount;
and generating the similarity between the historical item information and the target item information based on the normalized historical circulation amount, the normalized historical browsing amount, the historical circulation rate, the historical return rate, the normalized target circulation amount, the normalized target browsing amount, the target circulation rate and the target return rate.
8. A vehicle control apparatus for an article, comprising:
the system comprises an acquisition unit, a display unit and a display unit, wherein the acquisition unit is configured to acquire a historical item information set and target item information of an item, the historical item information in the historical item information set comprises a historical circulation amount, a historical browsing amount, a historical circulation rate, a historical return rate and a historical item transfer amount, and the target item information comprises a target circulation amount, a target browsing amount, a target circulation rate and a target return rate;
a generating unit configured to generate a similarity between the historical item information and the target item information based on a historical circulation amount, a historical browsing amount, a historical circulation rate and a historical return rate included by each historical item information in the historical item information set and the target circulation amount, the target browsing amount, the target circulation rate and the target return rate, so as to obtain a similarity set;
the extracting unit is configured to respond to the similarity meeting a preset condition in the similarity set, and extract historical item scheduling amount from historical item information corresponding to the similarity meeting the preset condition in the similarity set to obtain a historical item scheduling amount set;
a control unit configured to control the associated vehicle to perform an item scheduling operation based on the set of historical item scheduling amounts.
9. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110227089.5A CN112598337A (en) | 2021-03-02 | 2021-03-02 | Article-oriented vehicle control method, apparatus, device and computer readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110227089.5A CN112598337A (en) | 2021-03-02 | 2021-03-02 | Article-oriented vehicle control method, apparatus, device and computer readable medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112598337A true CN112598337A (en) | 2021-04-02 |
Family
ID=75207675
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110227089.5A Pending CN112598337A (en) | 2021-03-02 | 2021-03-02 | Article-oriented vehicle control method, apparatus, device and computer readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112598337A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112862415A (en) * | 2021-04-26 | 2021-05-28 | 北京每日优鲜电子商务有限公司 | Transportation vehicle scheduling method and device, electronic equipment and computer readable medium |
| CN114429365A (en) * | 2022-01-12 | 2022-05-03 | 北京京东振世信息技术有限公司 | Article sales information generation method and device, electronic equipment and computer medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106327116A (en) * | 2015-07-09 | 2017-01-11 | 阿里巴巴集团控股有限公司 | Method and device for carrying out regional inventory allocation on target articles |
| US20180101800A1 (en) * | 2016-10-12 | 2018-04-12 | Accenture Global Solutions Limited | Adaptive logistics platform for generating and updating schedules using natural language processing |
| CN111105195A (en) * | 2019-12-24 | 2020-05-05 | 北京每日优鲜电子商务有限公司 | Replenishment quantity determining method and device, computer equipment and storage medium |
| CN111932161A (en) * | 2020-10-12 | 2020-11-13 | 北京每日优鲜电子商务有限公司 | Vehicle scheduling method and device for articles, electronic equipment and computer medium |
| CN112184100A (en) * | 2020-09-09 | 2021-01-05 | 北京每日优鲜电子商务有限公司 | Article inventory monitoring method and device, electronic equipment and computer readable medium |
-
2021
- 2021-03-02 CN CN202110227089.5A patent/CN112598337A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106327116A (en) * | 2015-07-09 | 2017-01-11 | 阿里巴巴集团控股有限公司 | Method and device for carrying out regional inventory allocation on target articles |
| US20180101800A1 (en) * | 2016-10-12 | 2018-04-12 | Accenture Global Solutions Limited | Adaptive logistics platform for generating and updating schedules using natural language processing |
| CN111105195A (en) * | 2019-12-24 | 2020-05-05 | 北京每日优鲜电子商务有限公司 | Replenishment quantity determining method and device, computer equipment and storage medium |
| CN112184100A (en) * | 2020-09-09 | 2021-01-05 | 北京每日优鲜电子商务有限公司 | Article inventory monitoring method and device, electronic equipment and computer readable medium |
| CN111932161A (en) * | 2020-10-12 | 2020-11-13 | 北京每日优鲜电子商务有限公司 | Vehicle scheduling method and device for articles, electronic equipment and computer medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112862415A (en) * | 2021-04-26 | 2021-05-28 | 北京每日优鲜电子商务有限公司 | Transportation vehicle scheduling method and device, electronic equipment and computer readable medium |
| CN114429365A (en) * | 2022-01-12 | 2022-05-03 | 北京京东振世信息技术有限公司 | Article sales information generation method and device, electronic equipment and computer medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107944481B (en) | Method and apparatus for generating information | |
| CN110738436B (en) | Method and device for determining available inventory | |
| CN108810047B (en) | Method and device for determining information push accuracy rate and server | |
| CN110619078B (en) | Method and device for pushing information | |
| CN110866040B (en) | User portrait generation method, device and system | |
| CN113034090B (en) | Transportation equipment scheduling method and device, electronic equipment and computer readable medium | |
| CN112562229A (en) | Settlement device control method, settlement device control device, electronic device and computer readable medium | |
| CN112598337A (en) | Article-oriented vehicle control method, apparatus, device and computer readable medium | |
| CN112035753A (en) | Recommendation page generation method and device, electronic equipment and computer readable medium | |
| CN114202130A (en) | Flow transfer amount prediction multitask model generation method, scheduling method, device and equipment | |
| CN113610448A (en) | Article scheduling method and device, electronic equipment and computer readable medium | |
| CN112581241B (en) | Device control method, device, electronic device and computer readable medium | |
| CN114048931B (en) | Replenishment information generation method and device, electronic equipment and computer readable medium | |
| CN114066363A (en) | Order information processing method and device, electronic equipment and computer readable medium | |
| CN112102043B (en) | Item recommendation page generation method and device, electronic equipment and readable medium | |
| CN112559898B (en) | Item information sending method, item information sending device, electronic equipment and computer readable medium | |
| CN112182374B (en) | Inventory control method, apparatus, electronic device, and computer-readable medium | |
| CN111738632B (en) | Device control method, device, electronic device and computer readable medium | |
| CN112308378A (en) | Scheduling device control method, scheduling device control device, electronic device and computer readable medium | |
| CN112734309B (en) | Vehicle scheduling method, device, equipment and computer readable medium for article | |
| CN112308477A (en) | Inventory positioning method and device | |
| CN111385150A (en) | Method and device for acquiring information | |
| CN112547569B (en) | Article sorting equipment control method, device, equipment and computer readable medium | |
| CN110187987B (en) | Method and apparatus for processing requests | |
| CN112364232A (en) | Information generation method and device, electronic equipment and computer readable medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210402 |
|
| RJ01 | Rejection of invention patent application after publication |