Resource configuration method and apparatus, electronic device, and computer-readable storage medium

Abstract

The disclosure provides a resource configuration method and device, electronic equipment and computer readable storage medium, which can be applied to the fields of computer technology, data processing technology and logistics technology. The resource configuration method comprises: in response to receiving a resource configuration request, obtaining to-be-processed information and historical order information according to a current system time indicated by the resource configuration request; the to-be-processed information comprises current to-be-processed information corresponding to a current time period and historical to-be-processed information corresponding to a first historical time period, and the current time period and the first historical time period are determined according to the current system time; determining M influence coefficients and influence variables corresponding to the M influence coefficients according to the current to-be-processed information and the historical to-be-processed information; determining predicted order information according to the historical order information, the M influence coefficients and the influence variables corresponding to the M influence coefficients; and determining resource configuration information corresponding to a resource type to be configured according to the predicted order information.

Description

Technical Field

[0001] This disclosure relates to the fields of computer technology, data processing technology, and logistics technology, and more specifically, to a resource allocation method and apparatus, electronic equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] With the development of computer technology and data processing technology, logistics technology has also been widely applied.

[0003] Logistics refers to the planning, implementation, and control of the efficient and low-cost flow and storage of goods, services, and related information from the point of production to the point of consumption in order to meet user needs. In the logistics process, relevant resources need to be effectively allocated to facilitate the flow of goods, services, and related information.

[0004] In realizing the concept disclosed herein, the inventors discovered at least the following problems in the related technology: because the current allocation of related resources requires manual labor, the efficiency and accuracy of resource allocation cannot be guaranteed. Summary of the Invention

[0005] In view of the above, this disclosure provides a resource allocation method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

[0006] According to one aspect of this disclosure, a resource allocation method is provided, comprising: in response to receiving a resource allocation request, acquiring pending information and historical order information according to the current system time indicated by the resource allocation request, wherein the resource allocation request further includes a resource type to be configured, the pending information includes current pending information corresponding to the current time period and historical pending information corresponding to a first historical time period, the current time period and the first historical time period being determined based on the current system time; determining M influence coefficients and influence variables corresponding to each of the M influence coefficients based on the current pending information and the historical pending information, wherein M is a positive integer; determining predicted order information based on the historical order information, the M influence coefficients and the influence variables corresponding to each of the M influence coefficients; and determining resource allocation information corresponding to the resource type to be configured based on the predicted order information.

[0007] According to embodiments of this disclosure, the aforementioned current pending information includes at least first current coefficient information and second current coefficient information, and the aforementioned historical pending information includes at least first historical coefficient information, second historical coefficient information, and historical variable information.

[0008] According to embodiments of this disclosure, determining M influence coefficients and corresponding influence variables based on the current pending information and the historical pending information includes: determining a first ratio as a first influence coefficient, wherein the first ratio is determined based on the first current coefficient information and the first historical coefficient information; determining a second ratio as a second influence coefficient, wherein the second ratio is determined based on the second current coefficient information and the second historical coefficient information; determining a third influence coefficient based on the current system time; and determining the influence variables corresponding to the first influence coefficient, the second influence coefficient, and the third influence coefficient based on the historical variable information.

[0009] According to embodiments of this disclosure, the aforementioned historical order information includes actual historical order information and predicted historical order information corresponding to each of the N sub-historical time periods, where N is a positive integer.

[0010] According to embodiments of this disclosure, the method further includes, before determining the predicted order information based on the historical order information, the M influence coefficients, and the influence variables corresponding to each of the M influence coefficients: for each of the N sub-historical periods, determining a first difference based on the actual historical order information and the predicted historical order information corresponding to the sub-historical period; determining a second difference based on the actual historical order information and the first difference; determining a first product value corresponding to the sub-historical period based on the second difference; and determining an error assessment value based on the first product values ​​corresponding to each of the N sub-historical periods.

[0011] According to embodiments of this disclosure, determining the predicted order information based on the historical order information, the M influence coefficients, and the influence variables corresponding to each of the M influence coefficients includes: for each of the M influence coefficients, determining a second product value corresponding to the influence coefficient based on the influence coefficient and the influence variable corresponding to the influence coefficient; determining a first accumulated value based on the second product value corresponding to each of the M influence coefficients; determining a second accumulated value based on the historical order information and the first accumulated value; and determining the predicted order information based on the second accumulated value and the error assessment value.

[0012] According to an embodiment of this disclosure, when the resource type to be configured is a first resource type, determining the resource configuration information corresponding to the resource type to be configured based on the predicted order information includes: obtaining historical pending information corresponding to a second historical time period based on the first resource type, wherein the historical pending information includes the number of historical objects and the number of historical resources; determining a third ratio based on the number of historical objects and the number of historical resources; determining a fourth ratio based on the predicted order information and the third ratio; and determining the resource configuration information corresponding to the first resource type based on the fourth ratio.

[0013] According to an embodiment of this disclosure, when the resource type to be configured is a second resource type, determining the resource configuration information corresponding to the resource type to be configured based on the predicted order information includes: filtering the predicted order information to obtain predicted sub-order information corresponding to the second resource type; determining a fifth ratio based on the predicted sub-order information and a predetermined value; and determining the resource configuration information corresponding to the second resource type based on the fifth ratio.

[0014] According to embodiments of this disclosure, after determining the resource configuration information corresponding to the resource type to be configured based on the predicted order information: determining a predetermined resource configuration threshold corresponding to the resource type to be configured based on the resource type to be configured; and outputting a warning message in response to the relationship between the predetermined resource configuration threshold and the predicted resource configuration information not meeting a predetermined condition.

[0015] According to embodiments of this disclosure, the above-mentioned response to receiving a resource configuration request, and obtaining pending information and historical order information based on the current system time indicated by the resource configuration request, includes: in response to receiving the resource configuration request, determining a historical system time corresponding to the current system time; determining a first historical time period based on a first predetermined start time and the historical system time; determining the current time period based on a second predetermined start time and the current system time; and obtaining the historical pending information corresponding to the first historical time period and the current pending information corresponding to the current time period from a data source.

[0016] According to another aspect of this disclosure, a resource allocation apparatus is provided, comprising: an acquisition module, configured to, in response to receiving a resource allocation request, acquire pending information and historical order information according to the current system time indicated by the resource allocation request, wherein the resource allocation request further includes a resource type to be configured, and the pending information includes current pending information corresponding to the current time period and historical pending information corresponding to a first historical time period, wherein the current time period and the first historical time period are determined based on the current system time; a first determination module, configured to determine M influence coefficients and influence variables corresponding to each of the M influence coefficients based on the current pending information and the historical pending information, wherein M is a positive integer; a second determination module, configured to determine predicted order information based on the historical order information, the M influence coefficients and the influence variables corresponding to each of the M influence coefficients; and a third determination module, configured to determine resource allocation information corresponding to the resource type to be configured based on the predicted order information.

[0017] According to another aspect of this disclosure, an electronic device is provided, comprising: one or more processors; and a memory for storing one or more instructions, wherein, when executed by the one or more processors, the one or more processors cause the one or more processors to perform the method as described in this disclosure.

[0018] According to another aspect of this disclosure, a computer-readable storage medium is provided having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described in this disclosure.

[0019] According to another aspect of this disclosure, a computer program product is provided, which includes computer-executable instructions that, when executed, are used to perform the methods described in this disclosure.

[0020] According to embodiments of this disclosure, influence coefficients and influence variables are obtained by analyzing current and historical pending information. These coefficients and variables can be used to predict resource demand. Since the predicted order information is determined in real-time based on historical order information, influence coefficients, and influence variables, it can characterize today's total order volume. By combining historical order information, influence coefficients, and influence variables, effective prediction of future order information can be achieved, thus improving the accuracy of predicted order information determination. Furthermore, by determining resource configuration information corresponding to the type of resource to be configured based on the predicted order information, this at least partially overcomes the technical problem in related technologies where manual resource configuration is required, leading to a lack of efficiency and accuracy in resource allocation. This achieves effective prediction of resource configuration information, thereby improving the efficiency and accuracy of resource allocation. Attached Figure Description

[0021] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0022] Figure 1 This illustration schematically shows a system architecture to which the resource allocation method can be applied according to embodiments of the present disclosure;

[0023] Figure 2 A flowchart illustrating a resource allocation method according to an embodiment of the present disclosure is shown schematically;

[0024] Figure 3 This illustration schematically shows an example diagram of a business process according to an embodiment of the present disclosure;

[0025] Figure 4 This illustration schematically depicts an example of a process, according to an embodiment of the present disclosure, in response to receiving a resource configuration request, obtaining pending information and historical order information based on the current system time indicated by the resource configuration request.

[0026] Figure 5 This illustration schematically shows an example of a process for determining M influence coefficients and corresponding influence variables based on current information to be processed and historical information to be processed, according to an embodiment of the present disclosure.

[0027] Figure 6 This illustration schematically shows an example of a process for determining predicted order information based on historical order information, M influence coefficients, and influence variables corresponding to each of the M influence coefficients, according to an embodiment of the present disclosure.

[0028] Figure 7A This illustration schematically shows an example diagram of a process for determining resource configuration information corresponding to the type of resource to be configured based on predicted order information according to an embodiment of the present disclosure;

[0029] Figure 7B This illustration schematically shows an example diagram of a process for determining resource configuration information corresponding to the type of resource to be configured based on predicted order information, according to another embodiment of this disclosure.

[0030] Figure 8 An example schematic diagram of a display interface according to an embodiment of the present disclosure is shown;

[0031] Figure 9 A block diagram of a resource configuration apparatus according to an embodiment of the present disclosure is schematically shown; and

[0032] Figure 10 A block diagram of an electronic device suitable for implementing a resource allocation method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0033] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0034] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0035] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0036] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0037] In the embodiments disclosed herein, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.

[0038] In the embodiments disclosed herein, user authorization or consent is obtained before acquiring or collecting user personal information.

[0039] For example, after collecting information to be processed and historical order information, methods such as de-identification or anonymization can be used to de-identify your information in order to protect your information security.

[0040] In logistics scenarios, a grid station can refer to the terminal sorting and delivery station in a community group-buying business. A grid station serves as the basic unit for terminal sorting and delivery within a sorting warehouse, responsible for sorting and delivering goods to different group leaders in the surrounding area. Sorting refers to the process where, after goods arrive at the grid station, the grid station's sorting staff distributes the goods to the corresponding boxes.

[0041] Resources associated with grid stations may include distribution staff, delivery vehicles, and insulated boxes. Due to certain special circumstances, the demand for these resources can fluctuate significantly. For example, before the Dragon Boat Festival, increased sales of zongzi (sticky rice dumplings) lead to a greater demand for insulated boxes. Alternatively, before the Spring Festival, the difficulty in recruiting staff increases the demand for distribution staff.

[0042] In these special cases, the grid station administrators usually need to manually allocate the relevant resources, which makes it impossible to guarantee the efficiency and accuracy of resource allocation.

[0043] To at least partially address the technical problems existing in related technologies, this disclosure provides a resource allocation method and apparatus, electronic device, and computer-readable storage medium, which can be applied to the fields of computer technology, data processing technology, and logistics technology. The resource allocation method includes: in response to receiving a resource allocation request, acquiring pending information and historical order information according to the current system time indicated by the resource allocation request, wherein the resource allocation request further includes a resource type to be configured, and the pending information includes current pending information corresponding to the current time period and historical pending information corresponding to a first historical time period, the current time period and the first historical time period being determined based on the current system time; determining M influence coefficients and corresponding influence variables for each of the M influence coefficients based on the current pending information and the historical pending information, where M is a positive integer; determining predicted order information based on the historical order information, the M influence coefficients, and the corresponding influence variables for each of the M influence coefficients; and determining resource allocation information corresponding to the resource type to be configured based on the predicted order information.

[0044] Figure 1 The illustration schematically depicts a system architecture to which the resource allocation method can be applied according to embodiments of this disclosure. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0045] like Figure 1As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0046] Users can interact with server 105 via network 104 using at least one of the first terminal device 101, second terminal device 102, and third terminal device 103 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, second terminal device 102, and third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0047] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0048] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0049] It should be noted that the resource configuration method provided in this embodiment can generally be executed by server 105. Correspondingly, the resource configuration device provided in this embodiment can generally be located in server 105. The resource configuration method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the resource configuration device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0050] Alternatively, the resource configuration method provided in this embodiment of the present disclosure can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Correspondingly, the resource configuration device provided in this embodiment of the present disclosure can also be disposed in the first terminal device 101, the second terminal device 102, or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103.

[0051] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0052] It should be noted that the sequence numbers of the operations in the following methods are for descriptive purposes only and should not be considered as indicating the execution order of the operations. Unless explicitly stated otherwise, the method does not need to be executed in the exact order shown.

[0053] Figure 2 A flowchart illustrating a resource configuration method according to an embodiment of the present disclosure is shown schematically.

[0054] like Figure 2 As shown, the resource configuration method 200 includes operations S210 to S240.

[0055] In operation S210, in response to receiving a resource configuration request, pending information and historical order information are obtained according to the current system time indicated by the resource configuration request. The resource configuration request also includes the type of resource to be configured, and the pending information includes the current pending information corresponding to the current time period and the historical pending information corresponding to the first historical time period. The current time period and the first historical time period are determined according to the current system time.

[0056] In operation S220, based on the current information to be processed and the historical information to be processed, determine M influence coefficients and the influence variables corresponding to each of the M influence coefficients, where M is a positive integer.

[0057] In operation S230, based on historical order information, M influence coefficients, and the influence variables corresponding to each of the M influence coefficients, the predicted order information is determined.

[0058] In operation S240, based on the predicted order information, the resource configuration information corresponding to the resource type to be configured is determined.

[0059] According to embodiments of this disclosure, the code for generating a resource configuration request can be pre-written into a script. In response to detecting a user's resource configuration operation, the current system time and the type of resource to be configured can be obtained. The type of resource to be configured can be used to characterize the type of resource configuration the user needs to perform. For example, the type of resource to be configured can include at least one of the following: a first resource type and a second resource type. The specific content of the first resource type and the second resource type can be set according to actual business needs and is not limited here. For example, the first resource type can include the number of broadcasters or the number of delivery vehicles, etc. Alternatively, the second resource type can include turnover baskets, refrigerated insulated boxes, and frozen insulated boxes, etc.

[0060] According to embodiments of this disclosure, the client can run the script to generate a resource configuration request message based on the current system time and the type of resource to be configured. The client can send the resource configuration request message to the server, so that the server can process the pending information corresponding to the resource configuration operation and perform resource configuration based on the resource configuration request message.

[0061] According to embodiments of this disclosure, after receiving a resource configuration request, the server can determine the current system time in the resource configuration request. After obtaining the current system time, the server can determine the current time period and the first historical time period corresponding to the current system time. For example, if the current system time is "September 2, 2023, 08:00", then the current time period can be determined as "September 2, 2023, 07:00 to September 1, 2023, 08:00", and the first historical time period is "September 1, 2023, 08:00 to September 2, 2023, 08:00".

[0062] According to embodiments of this disclosure, after obtaining the current time period and the first historical time period, current pending information can be obtained from the data source based on the current time period, and historical pending information and historical order information can be obtained from the data source based on the first historical time period. The data source may include at least one of the following: a local database, a cloud database, and network resources. For example, a data interface can be invoked. The data interface is used to obtain the current pending information corresponding to the current time period and the historical pending information and historical order information corresponding to the first historical time period from the data source.

[0063] According to embodiments of this disclosure, after obtaining current pending information and historical pending information, M influence coefficients can be determined. The influence coefficients include at least a first influence coefficient, a second influence coefficient, and a third influence coefficient. For example, the current pending information may include at least first current coefficient information and second current coefficient information. The historical pending information may include first historical coefficient information and second historical coefficient information. Based on this, a first influence coefficient can be determined according to the first current coefficient information and the first historical coefficient information. A second influence coefficient is determined according to the second current coefficient information and the second historical coefficient information. A third influence coefficient is determined according to the current system time.

[0064] According to embodiments of this disclosure, after obtaining historical information to be processed, the influencing variables corresponding to each of the M influence coefficients can be determined. For example, the historical information to be processed may include historical variable information. The historical variable information includes at least first historical variable information, second historical variable information, and third historical variable information. Based on this, a first influencing variable corresponding to a first influence coefficient can be determined according to the first historical variable information. A second influencing variable corresponding to a second influence coefficient can be determined according to the second historical variable information. A third influencing variable corresponding to a third influence coefficient can be determined according to the third historical variable information.

[0065] According to embodiments of this disclosure, after obtaining M influence coefficients and their corresponding influence variables, the product value between each of the M influence coefficients and its corresponding influence variable can be determined. After determining the product value for each influence coefficient, these product values ​​can be accumulated to obtain a cumulative value. Based on this cumulative value and historical order information, predicted order information can be determined.

[0066] According to embodiments of this disclosure, after obtaining predicted order information, resource configuration information corresponding to the resource type to be configured can be determined based on the predicted order information. For example, if the resource type to be configured is a first resource type, a second historical time period corresponding to the first resource type can be determined, and the resource configuration information corresponding to the first resource type can be determined based on the number of historical objects and the number of historical resources obtained during the second historical time period. Alternatively, if the resource type to be configured is a second resource type, the predicted order information can be filtered, and the resource configuration information corresponding to the second resource type can be determined based on the filtered order information and a predetermined value. The predetermined value can be set according to the specific resource type.

[0067] According to embodiments of this disclosure, influence coefficients and influence variables are obtained by analyzing current and historical pending information. These coefficients and variables can be used to predict resource demand. Since the predicted order information is determined in real-time based on historical order information, influence coefficients, and influence variables, it can characterize today's total order volume. By combining historical order information, influence coefficients, and influence variables, effective prediction of future order information can be achieved, thus improving the accuracy of predicted order information determination. Furthermore, by determining resource configuration information corresponding to the type of resource to be configured based on the predicted order information, this at least partially overcomes the technical problem in related technologies where manual resource configuration is required, leading to a lack of efficiency and accuracy in resource allocation. This achieves effective prediction of resource configuration information, thereby improving the efficiency and accuracy of resource allocation.

[0068] The following is for reference. Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7A , Figure 7B and Figure 8 The resource allocation method 200 according to an embodiment of the present invention will be further described.

[0069] Figure 3 An example schematic diagram of a business process according to an embodiment of this disclosure is shown.

[0070] like Figure 3 As shown, the business process may include the e-commerce order center, warehouse management system, grid station, and group leader terminal.

[0071] In the 300 system, the online store's order center allows users to place orders and automatically creates production tasks. In response to the creation of production tasks in the online store's order center, the warehouse management system can perform warehouse distribution and delivery. In response to the warehouse management system completing warehouse delivery, the grid station can perform grid station receiving, grid station distribution, and grid station delivery. In response to the grid station completing grid station delivery, the group leader's terminal can perform group leader receiving and allow users to pick up their goods.

[0072] According to embodiments of this disclosure, operation S210 may include the following operations.

[0073] In response to receiving a resource configuration request, the system determines the historical system time corresponding to the current system time. Based on a first predetermined start time and the historical system time, a first historical time period is determined. Based on a second predetermined start time and the current system time, the current time period is determined. Historical pending information corresponding to the first historical time period and current pending information corresponding to the current time period are retrieved from the data source.

[0074] According to embodiments of this disclosure, after receiving a resource configuration request, the current time period can be determined based on a second predetermined start time and the current system time. The second predetermined start time can be set according to actual business needs and is not limited here. For example, the second predetermined start time can be set to "September 2, 2023, 00:00" and the current system time can be "September 2, 2023, 08:00". Based on this, the current time period can be determined as "September 2, 2023, 00:00 to September 2, 2023, 08:00".

[0075] According to embodiments of this disclosure, a historical system time corresponding to the current system time can be determined based on the current system time. For example, if the current system time is "September 2, 2023, 08:00", then the historical system time can be determined as "September 1, 2023, 08:00".

[0076] According to embodiments of this disclosure, after obtaining the historical system time, a first historical time period can be determined based on a first predetermined start time and the historical system time. The first predetermined start time can be set according to actual business needs and is not limited here. For example, the first predetermined start time can be set to "September 1, 2023, 00:00" and the historical system time can be set to "September 1, 2023, 08:00". Based on this, the first historical time period can be determined as "September 1, 2023, 00:00 to September 1, 2023, 08:00".

[0077] According to embodiments of this disclosure, since the first historical time period is determined based on a first predetermined start time and a historical system time, and the historical system time is determined based on the current system time, obtaining historical pending information from the data source based on the first historical time period facilitates subsequent analysis and processing of the data for the first historical time period, which helps to obtain historical order change trends. Since the current time period is determined based on a second predetermined start time and the current system time, obtaining current pending information from the data source based on the current time period facilitates subsequent analysis and processing of the data for the current time period, which helps to predict the current order status, thereby providing a data foundation for the subsequent resource allocation process.

[0078] Figure 4 The illustration shows an example of a process according to an embodiment of the present disclosure of obtaining pending information and historical order information based on the current system time indicated by the resource configuration request in response to receiving a resource configuration request.

[0079] like Figure 4As shown, in step 400, in response to receiving a resource configuration request 401, a historical system time 403 corresponding to the current system time 402 can be determined. A first historical time period 405 is determined based on a first predetermined start time 404 and the historical system time 403. The current time period 407 is determined based on a second predetermined start time 406 and the current system time 402.

[0080] Based on this, the historical pending information 408 corresponding to the first historical time period 405 and the current pending information 409 corresponding to the current time period 407 can be obtained from the data source.

[0081] According to embodiments of this disclosure, the current information to be processed includes at least first current coefficient information and second current coefficient information, and the historical information to be processed includes at least first historical coefficient information, second historical coefficient information and historical variable information.

[0082] According to embodiments of this disclosure, operation S220 may include the following operations.

[0083] The first ratio is determined as the first influence coefficient, which is determined based on the first current coefficient information and the first historical coefficient information. The second ratio is determined as the second influence coefficient, which is determined based on the second current coefficient information and the second historical coefficient information. A third influence coefficient is determined based on the current system time. Influence variables corresponding to the first, second, and third influence coefficients are determined based on historical variable information.

[0084] According to embodiments of this disclosure, historical variable information may include at least first historical variable information corresponding to a first influence coefficient, second historical variable information corresponding to a second influence coefficient, and third historical variable information corresponding to a third influence coefficient.

[0085] According to embodiments of this disclosure, the first influence coefficient can be set according to actual business needs, and is not limited herein. For example, the first influence coefficient can be used to characterize the discount strength coefficient. The first current coefficient information can be "a total of 10,000 coupons worth 10 yuan were claimed today", and the first historical coefficient information can be "a total of 10,000 coupons worth 5 yuan were claimed yesterday". Based on this, the first ratio can be determined to be 2 according to the first current coefficient information and the first historical coefficient information, and the first influence coefficient can be determined to be 2 according to the first ratio.

[0086] According to embodiments of this disclosure, after obtaining the first influence coefficient, the first influence variable can be determined based on the first historical variable information. For example, if the current system time indicates that today is Sunday, then the first historical variable information can be "how many orders increase for each Sunday within 30 days when the discount is doubled compared to Saturday; or how many orders decrease for each discount is halved." Based on this, the first influence variable for this week can be determined according to the known changes in the first historical variable information.

[0087] According to embodiments of this disclosure, the second influence coefficient can be set according to actual business needs, and is not limited herein. For example, since the conversion rate of product clicks to orders is approximately 15%, product clicks can be used as the second influence coefficient. The second current coefficient information can be "total product clicks today are 30,000", and the second historical coefficient information can be "total product clicks yesterday are 10,000". Based on this, the second ratio can be determined to be 3 according to the second current coefficient information and the second historical coefficient information, and the second influence coefficient can be determined to be 3 according to this second ratio.

[0088] According to embodiments of this disclosure, after obtaining the second influence coefficient, the second influence variable can be determined based on the second historical variable information. For example, the second historical variable information can be "the change in the number of clicks for every n-fold increase in clicks over four periods." Based on this, the second influence variable for this week can be determined according to the known changes in the second historical variable information.

[0089] According to embodiments of this disclosure, the third influence coefficient can be set according to actual business needs and is not limited herein. Since community group buying scenarios involve a large number of daily necessities, fruits and vegetables, etc., they are significantly affected by holidays. For example, sales of fruits and vegetables are usually higher on Saturdays, while order volume drops on weekdays. Therefore, the third influence coefficient can be used to characterize whether it is a holiday. For example, if the current system time indicates that today is Saturday, Sunday, or a public holiday, the third influence coefficient can be set to 1. Alternatively, if the current system time indicates that today is a weekday, the third influence coefficient can be set to 0.

[0090] According to embodiments of this disclosure, after obtaining the third influence coefficient, the third influence variable can be determined based on the third historical variable information. For example, if the current system time indicates that today is Saturday, the third historical variable information could be "the percentage increase in order volume on Saturday compared to Friday over four periods." Based on this, the third influence variable for this week can be determined according to the known changes in the third historical variable information.

[0091] According to embodiments of this disclosure, a first ratio is determined based on first current coefficient information and first historical coefficient information, and a first influence coefficient is determined based on the first ratio. Therefore, the first influence coefficient can be used to quantify the comparative relationship between the first current coefficient information and the first historical coefficient information. A second ratio is determined based on second current coefficient information and second historical coefficient information, and a second influence coefficient is determined based on the second ratio. Therefore, the second influence coefficient can be used to quantify the comparative relationship between the second current coefficient information and the second historical coefficient information. A third influence coefficient is determined based on the current system time, thus the third influence coefficient can be used to measure the degree of influence at the current time. Furthermore, by determining the influence variables corresponding to each influence coefficient based on historical variable information, the influence coefficients and corresponding influence variables can be associated based on historical variable information, which helps to improve the accuracy of subsequent order prediction determination.

[0092] Figure 5 The illustration shows an example diagram of a process for determining M influence coefficients and corresponding influence variables based on current information to be processed and historical information to be processed, according to an embodiment of the present disclosure.

[0093] like Figure 5 As shown, in 500, the current information to be processed may include at least the first current coefficient information 501_1 and the second current coefficient information 501_2. The historical information to be processed may include at least the first historical coefficient information 502_1, the second historical coefficient information 502_2, and the historical variable information 509.

[0094] A first ratio 503 can be determined based on the first current coefficient information 501_1 and the first historical coefficient information 502_1, and this first ratio 503 is designated as the first influence coefficient 504. A second ratio 505 can be determined based on the second current coefficient information 501_2 and the second historical coefficient information 502_2, and this second ratio 505 is designated as the second influence coefficient 506. A third influence coefficient 508 is determined based on the current system time 507.

[0095] Based on this, the influence variables 510 corresponding to the first influence coefficient 504, the second influence coefficient 506, and the third influence coefficient 508 can be determined according to the historical variable information 509.

[0096] According to embodiments of this disclosure, historical order information includes actual historical order information and predicted historical order information corresponding to each of N sub-historical time periods, where N is a positive integer.

[0097] According to embodiments of this disclosure, the resource allocation method 200 may further include the following operations.

[0098] For each of the N sub-historical time periods, a first difference is determined based on the actual historical order information and the predicted historical order information corresponding to that sub-historical time period. A second difference is determined based on the actual historical order information and the first difference. A first product value corresponding to the sub-historical time period is determined based on the second difference. An error assessment value is determined based on the first product values ​​corresponding to each of the N sub-historical time periods.

[0099] According to embodiments of this disclosure, since an order information prediction process is performed every hour from 12:00 to 22:00, the actual historical order information for the current hourly period and the predicted historical order information obtained through the resource allocation method are obtained every hour. For example, the sub-historical time period can be "12:00~13:00", "13:00~14:00", ..., "21:00~22:00".

[0100] According to an embodiment of this disclosure, at 13:00, the order information between 12:00 and 13:00 changes from unknown to known, and the difference between the predicted value and the actual value for the current hour can be obtained, thereby determining the error assessment value, so that the predicted order information can be corrected according to the error assessment value in the future.

[0101] According to an embodiment of this disclosure, the error assessment value is determined as shown in equation (1).

[0102]

[0103] Among them, y i This represents the actual historical order information corresponding to the sub-historical period. This represents the predicted historical order information corresponding to the sub-historical time period. Characterizing the first difference, The first product value is represented by ε, and the error assessment value is represented by ε. The smaller the error assessment value, the more accurate the predicted order information.

[0104] According to embodiments of this disclosure, since the first difference is determined based on the actual historical order information and the predicted historical order information corresponding to the sub-historical period, the first difference can be used to characterize the difference between the actual historical order information and the predicted historical order information. Since the second difference is determined based on the actual historical order information and the first difference, the second difference can be used to further determine the change in the difference. Furthermore, since the first product value corresponding to the sub-historical period is determined based on the second difference, the error assessment value is determined based on the first product value corresponding to each of the N sub-historical periods. The error assessment value is obtained by summarizing the effects of multiple sub-historical periods; therefore, the error assessment value can be used to more accurately assess the error between the actual historical order information and the predicted historical order information.

[0105] According to embodiments of this disclosure, operation S230 may include the following operations.

[0106] For each of the M influence coefficients, determine the second product value corresponding to the influence coefficient based on the coefficient and the corresponding influencing variable. Determine the first accumulated value based on the second product values ​​corresponding to each of the M influence coefficients. Determine the second accumulated value based on historical order information and the first accumulated value. Determine the predicted order information based on the second accumulated value and the error assessment value.

[0107] According to embodiments of this disclosure, after obtaining M influence coefficients and the corresponding influence variables for each of the M influence coefficients, a second product value between the influence coefficient and the corresponding influence variable can be determined for each influence coefficient. For example, a first second product value between a first influence coefficient and a first influence variable can be determined, a second second product value between a second influence coefficient and a second influence variable can be determined, and a third second product value between a third influence coefficient and a third influence variable can be determined.

[0108] According to embodiments of this disclosure, after obtaining the second product value corresponding to each influence coefficient, a first accumulated value can be determined based on the second product value corresponding to each influence coefficient. For example, the first accumulated value can be the sum of a first second product value, a second second product value, and a third second product value.

[0109] According to embodiments of this disclosure, after obtaining a first accumulated value, a second accumulated value can be determined based on historical order information and the first accumulated value. Based on this, predicted order information can be determined based on an error assessment value and the second accumulated value.

[0110] According to embodiments of this disclosure, the predicted order information can be determined by using historical order information as a benchmark, taking various factors affecting the number of orders as variables, and using the linear regression algorithm shown in equation (2) below.

[0111] y′=α+β1x1+β2x2+β3x3+ε (2)

[0112] Where y′ represents predicted order information, α represents historical order information, β1 represents the first influence coefficient (e.g., discount coefficient), x1 represents the first influence variable (e.g., discount variable), β2 represents the second influence coefficient (e.g., click-through rate per item coefficient), x2 represents the second influence variable (e.g., click-through rate per item variable), β3 represents the third influence coefficient (e.g., holiday / non-holiday coefficient), x3 represents the third influence variable (e.g., holiday / non-holiday variable), and ε represents the error assessment value.

[0113] According to embodiments of this disclosure, a second product value is determined based on the influence coefficient and the corresponding influence variable, and a first accumulated value is determined based on the second product value corresponding to each influence coefficient. The first accumulated value can be used to accumulate the contributions of different influence coefficients. Based on this, predicted order information is determined based on the first accumulated value, historical order information, and error assessment value. This comprehensively considers different influence coefficients, the corresponding influence variables, and the error assessment value. Since the error assessment value can be used to more accurately assess the error between actual historical order information and predicted historical order information, the accuracy of the predicted order information is improved.

[0114] Figure 6 The illustration shows an example diagram of a process for determining predicted order information based on historical order information, M influence coefficients, and influence variables corresponding to each of the M influence coefficients, according to an embodiment of the present disclosure.

[0115] like Figure 6 As shown in section 600, based on the influence coefficient 601 and the corresponding influence variable 602, the second product value 603 corresponding to the influence coefficient 601 can be determined. Based on the second product values ​​603 corresponding to each of the M influence coefficients 601, the first accumulated value 604 is determined. Based on historical order information 605 and the first accumulated value 604, the second accumulated value 606 is determined. On this basis, based on the second accumulated value 606 and the error assessment value 607, the predicted order information 608 is determined.

[0116] According to embodiments of this disclosure, when the resource type to be configured is a first resource type, operation S240 may include the following operations.

[0117] Based on the first resource type, obtain the historical pending information corresponding to the second historical time period, whereby the historical pending information includes the number of historical objects and the number of historical resources. Based on the number of historical objects and the number of historical resources, determine the third ratio. Based on the predicted order information and the third ratio, determine the fourth ratio. Based on the fourth ratio, determine the resource configuration information corresponding to the first resource type.

[0118] According to embodiments of this disclosure, the first resource type may include the number of broadcasting employees or the number of delivery vehicles, etc. The second historical period can be set according to actual business needs and is not limited thereto. For example, the second historical period may be the past 7 days.

[0119] According to embodiments of this disclosure, when the first resource type is the number of broadcast employees, the historical pending information corresponding to the second historical time period can be determined based on the first resource type. For example, the historical pending information may include the number of historical objects as "the total number of broadcast employees in the past 7 days" and the number of historical resources as "the total number of broadcast items in the past 7 days". A third ratio can be determined based on the number of historical objects and the number of historical resources as "the total number of broadcast items in the past 7 days / the total number of broadcast employees in the past 7 days" (or employee efficiency). Based on this, a fourth ratio can be determined based on the predicted order information and the third ratio as "predicted order information / employee efficiency". After obtaining the fourth ratio, it can be rounded to obtain the resource configuration information corresponding to the number of broadcast employees.

[0120] According to embodiments of this disclosure, when the first resource type is the number of delivery vehicles, historical pending information corresponding to the second historical period can be determined based on the first resource type. For example, the historical pending information may include the number of historical objects as "total number of shipments in the last 7 days" and the number of historical resources as "total number of vehicles in the last 7 days". A third ratio, "total number of shipments in the last 7 days / total number of vehicles in the last 7 days" (or vehicle efficiency), can be determined based on the number of historical objects and the number of historical resources. Based on this, a fourth ratio, "predicted order information / vehicle efficiency," can be determined based on the predicted order information and the third ratio. After obtaining the fourth ratio, it can be rounded to obtain resource configuration information corresponding to the number of delivery vehicles.

[0121] According to embodiments of this disclosure, when the resource type to be configured is a first resource type, the number of historical objects and the number of historical resources corresponding to a second historical period are obtained based on the first resource type. A third ratio is determined based on the number of historical objects and the number of historical resources. A fourth ratio is determined based on the predicted order information and the third ratio. Then, resource configuration information corresponding to the first resource type is determined based on the fourth ratio. This allows for automatic adjustment of resource configuration based on historical data and prediction results. Because predicted order information can be obtained in real time, excessive resource configuration is avoided, thus reducing operating costs and improving the ability to respond to changes and the initiative of the grid station. Furthermore, since predicted order information can accurately represent the number of orders today, resource configuration information can provide a basis for resource configuration for the grid station's maintenance personnel, which is conducive to ensuring that goods are delivered as early as possible, thereby improving the on-time delivery rate.

[0122] Figure 7A The illustration shows an example diagram of a process for determining resource configuration information corresponding to the type of resource to be configured based on predicted order information according to an embodiment of the present disclosure.

[0123] like Figure 7AAs shown in 700A, when the resource type to be configured is the first resource type 701, historical pending information 702 corresponding to the second historical time period can be obtained based on the first resource type 701. The historical pending information 702 includes the number of historical objects 702_1 and the number of historical resources 702_2. Based on the number of historical objects 702_1 and the number of historical resources 702_2, a third ratio 703 is determined. Based on the predicted order information 704 and the third ratio 703, a fourth ratio 705 is determined. On this basis, resource configuration information 706 corresponding to the first resource type 701 can be determined based on the fourth ratio 705.

[0124] According to embodiments of this disclosure, when the resource type to be configured is a second resource type, operation S240 may include the following operations.

[0125] The predicted order information is filtered to obtain the predicted sub-order information corresponding to the second resource type. Based on the predicted sub-order information and the pre-order values, the fifth ratio is determined. Based on the fifth ratio, the resource configuration information corresponding to the second resource type is determined.

[0126] According to embodiments of this disclosure, the second resource type may include turnover baskets, refrigerated insulated boxes, and frozen insulated boxes, etc. The predetermined values ​​can be set according to actual business needs and are not limited herein. For example, the predetermined values ​​can be set based on the object volume.

[0127] According to embodiments of this disclosure, when the second resource type is a turnover basket, the predicted order information can be filtered based on the temperature layer information corresponding to the room temperature object to obtain the predicted sub-order information corresponding to the room temperature object, i.e., the number of room temperature objects. A predetermined value can be set to 20 based on the object volume of the room temperature object. Based on this, a fifth ratio can be determined as "predicted sub-order information corresponding to the room temperature object / 20" according to the predicted sub-order information and the predetermined value. After obtaining the fifth ratio, if a remainder exists, the fifth ratio can be incremented by 1 to obtain the resource configuration information corresponding to the turnover basket.

[0128] According to embodiments of this disclosure, when the second resource type is a refrigerated insulated box, the predicted order information can be filtered based on the temperature information corresponding to the refrigerated object to obtain the predicted sub-order information corresponding to the refrigerated object, i.e., the number of refrigerated objects. A predetermined value can be set to 35 based on the object volume of the refrigerated object. Based on this, a fifth ratio can be determined as "predicted sub-order information corresponding to the refrigerated object / 35" according to the predicted sub-order information and the predetermined value. After obtaining the fifth ratio, if there is a remainder, the fifth ratio can be incremented by 1 to obtain the resource configuration information corresponding to the refrigerated insulated box.

[0129] According to embodiments of this disclosure, when the second resource type is a freezer / insulated box, the predicted order information can be filtered based on the temperature information corresponding to the frozen object to obtain the predicted sub-order information corresponding to the frozen object, i.e., the number of frozen objects. A predetermined value can be set to 25 based on the object volume of the frozen object. Based on this, a fifth ratio can be determined as "predicted sub-order information corresponding to the frozen object / 35" according to the predicted sub-order information and the predetermined value. After obtaining the fifth ratio, if a remainder exists, the fifth ratio can be incremented by 1 to obtain the resource configuration information corresponding to the freezer / insulated box.

[0130] According to embodiments of this disclosure, when the resource type to be configured is a second resource type, predicted sub-order information corresponding to the second resource type is obtained by filtering the order information. A fifth ratio is determined based on the predicted sub-order information and a predetermined value. Based on the fifth ratio, resource configuration information corresponding to the second resource type is determined, thereby enabling automatic adjustment of resource configuration based on historical data and prediction results. Since predicted order information can be obtained in real time, excessive resource configuration is avoided, thus reducing operating costs and improving the ability to respond to changes and the initiative of the grid station. Furthermore, because predicted order information can accurately represent the number of orders for the day, resource configuration information can provide a basis for resource configuration for grid station maintenance personnel, which is conducive to ensuring that goods are delivered as early as possible, thereby improving the on-time delivery rate.

[0131] Figure 7B The illustration shows an example diagram of a process for determining resource configuration information corresponding to the type of resource to be configured based on predicted order information, according to another embodiment of the present disclosure.

[0132] like Figure 7B As shown in 700B, when the resource type to be configured is the second resource type 707, the predicted order information 708 can be filtered to obtain the predicted sub-order information 709 corresponding to the second resource type 707. Based on the predicted sub-order information 709 and the predetermined value 710, the fifth ratio 711 is determined. On this basis, the resource configuration information 712 corresponding to the second resource type 707 can be determined according to the fifth ratio 711.

[0133] According to embodiments of this disclosure, the resource allocation method 200 may further include the following operations.

[0134] Based on the type of resource to be configured, a predetermined resource configuration threshold corresponding to that type is determined. If the relationship between the predetermined resource configuration threshold and the predicted resource configuration information does not meet a predetermined condition, an early warning message is output.

[0135] According to embodiments of this disclosure, after obtaining resource configuration information corresponding to the type of resource to be configured, production prediction can be performed on the resources corresponding to the type of resource to be configured based on the resource configuration information. For example, a predetermined resource configuration threshold can be determined based on the type of resource to be configured. The predetermined resource configuration threshold can be set according to actual business needs and is not limited here. For example, the predetermined resource configuration threshold can be determined based on historical resource configuration information and a target preset value, and the target prediction value can be set to 30%.

[0136] According to embodiments of this disclosure, after obtaining a predetermined resource configuration threshold, it can be determined whether the relationship between the predetermined resource configuration threshold and the predicted resource configuration information meets predetermined conditions. The predetermined conditions can be set according to actual business needs and are not limited here. The predetermined conditions can be set to the predicted resource configuration information being less than the predetermined resource configuration threshold. For example, if the predicted resource configuration information is less than the predetermined resource configuration threshold, resource configuration corresponding to the type of resource to be configured can be performed. Alternatively, if the predicted resource configuration information is greater than or equal to the predetermined resource configuration threshold, a warning message can be output through the application's display interface, and a notification can be sent to the grid station operators via email. The warning message can be set according to actual business needs and is not limited here. For example, the warning message can be "The predicted resource configuration information does not meet the predetermined conditions!".

[0137] According to the embodiments of this disclosure, since the predetermined resource configuration threshold is determined based on the type of resource to be configured, by outputting early warning information when the relationship between the predetermined resource configuration threshold and the predicted resource configuration information does not meet the predetermined conditions, the operation and maintenance personnel can be promptly prompted to adjust the resource configuration strategy, which is conducive to the normal operation of the business.

[0138] Figure 8 An example schematic diagram of a display interface according to an embodiment of the present disclosure is shown.

[0139] like Figure 8 As shown, in 800, the display interface 800 may include a production monitoring area 810, a production forecasting area 820, and an information notification area 830. The production monitoring area 810 may include a warehouse dispatch progress display sub-area 811, a distribution progress display sub-area 812, and a delivery completion progress display sub-area 813. The production forecasting area 820 may include a batch order forecasting display sub-area 821 and a distribution container forecasting display sub-area 822. The information notification area 830 may include a warning information display sub-area 831.

[0140] The above are merely exemplary embodiments, but are not limited thereto. Other resource allocation methods known in the art may also be included, as long as they can improve the efficiency and accuracy of resource allocation.

[0141] Figure 9 A block diagram of a resource configuration apparatus according to an embodiment of the present disclosure is shown schematically.

[0142] like Figure 9 As shown, the resource allocation device 900 may include an acquisition module 910, a first determination module 920, a second determination module 930, and a third determination module 940.

[0143] The acquisition module 910 is used to respond to receiving a resource configuration request and acquire pending information and historical order information according to the current system time indicated by the resource configuration request. The resource configuration request also includes the type of resource to be configured, and the pending information includes the current pending information corresponding to the current time period and the historical pending information corresponding to the first historical time period. The current time period and the first historical time period are determined according to the current system time.

[0144] The first determining module 920 is used to determine M influence coefficients and the influence variables corresponding to each of the M influence coefficients based on the current information to be processed and the historical information to be processed, where M is a positive integer.

[0145] The second determining module 930 is used to determine the predicted order information based on historical order information, M influence coefficients, and the influence variables corresponding to each of the M influence coefficients.

[0146] The third determination module 940 is used to determine the resource configuration information corresponding to the type of resource to be configured based on the predicted order information.

[0147] According to embodiments of this disclosure, the current information to be processed includes at least first current coefficient information and second current coefficient information, and the historical information to be processed includes at least first historical coefficient information, second historical coefficient information and historical variable information.

[0148] According to embodiments of this disclosure, the first determining module 920 may include a first determining unit, a second determining unit, a third determining unit, and a fourth determining unit.

[0149] The first determining unit is used to determine the first ratio as the first influence coefficient, wherein the first ratio is determined based on the first current coefficient information and the first historical coefficient information.

[0150] The second determining unit is used to determine the second ratio as the second influence coefficient, wherein the second ratio is determined based on the second current coefficient information and the second historical coefficient information.

[0151] The third determining unit is used to determine the third influence coefficient based on the current system time.

[0152] The fourth determining unit is used to determine the influencing variables corresponding to the first, second, and third influence coefficients based on historical variable information.

[0153] According to embodiments of this disclosure, historical order information includes actual historical order information and predicted historical order information corresponding to each of N sub-historical time periods, where N is a positive integer.

[0154] According to embodiments of this disclosure, the resource allocation device 900 may further include a fourth determining module, a fifth determining module, a sixth determining module, and a seventh determining module.

[0155] The fourth determination module is used to determine the first difference for each of the N sub-historical time periods based on the actual historical order information and the predicted historical order information corresponding to the sub-historical time period.

[0156] The fifth determination module is used to determine the second difference based on the actual historical order information and the first difference.

[0157] The sixth determining module is used to determine the first product value corresponding to the sub-historical period based on the second difference.

[0158] The seventh determination module is used to determine the error assessment value based on the first product value corresponding to each of the N sub-historical time periods.

[0159] According to embodiments of this disclosure, the second determining module 930 may include a fifth determining unit, a sixth determining unit, a seventh determining unit, and an eighth determining unit.

[0160] The fifth determining unit is used to determine the second product value corresponding to each of the M influence coefficients, based on the influence coefficient and the influence variable corresponding to the influence coefficient.

[0161] The sixth determining unit is used to determine the first accumulated value based on the second product value corresponding to each of the M influence coefficients.

[0162] The seventh determining unit is used to determine the second accumulated value based on historical order information and the first accumulated value.

[0163] The eighth determining unit is used to determine the predicted order information based on the second accumulated value and the error evaluation value.

[0164] According to embodiments of this disclosure, when the resource type to be configured is a first resource type, the third determining module 940 may include a first obtaining unit, a ninth determining unit, a tenth determining unit, and an eleventh determining unit.

[0165] The first acquisition unit is used to acquire historical pending information corresponding to the second historical period according to the first resource type, wherein the historical pending information includes the number of historical objects and the number of historical resources.

[0166] The ninth determining unit is used to determine the third ratio based on the number of historical objects and the number of historical resources.

[0167] The tenth determining unit is used to determine the fourth ratio based on the predicted order information and the third ratio.

[0168] The eleventh determining unit is used to determine the resource configuration information corresponding to the first resource type based on the fourth ratio.

[0169] According to embodiments of this disclosure, when the resource type to be configured is a second resource type, the third determining module 940 may include a filtering unit, a twelfth determining unit, and a thirteenth determining unit.

[0170] The filtering unit is used to filter the predicted order information to obtain the predicted sub-order information corresponding to the second resource type.

[0171] The twelfth determining unit is used to determine the fifth ratio based on the predicted sub-order information and the predetermined value.

[0172] The thirteenth determining unit is used to determine the resource configuration information corresponding to the second resource type based on the fifth ratio.

[0173] According to embodiments of this disclosure, the resource allocation device 900 may further include an eighth determination module and an output module.

[0174] The eighth determination module is used to determine the predetermined resource configuration threshold corresponding to the resource type to be configured.

[0175] The output module is used to output early warning information in response to the fact that the relationship between the predetermined resource configuration threshold and the predicted resource configuration information does not meet the predetermined conditions.

[0176] According to embodiments of this disclosure, the acquisition module 910 may include a fourteenth determining unit, a fifteenth determining unit, a sixteenth determining unit, and a second acquisition unit.

[0177] The fourteenth determining unit is used to determine the historical system time corresponding to the current system time in response to receiving a resource configuration request.

[0178] The fifteenth determining unit is used to determine the first historical time period based on the first predetermined start time and the historical system time.

[0179] The sixteenth determining unit is used to determine the current time period based on the second predetermined start time and the current system time.

[0180] The second acquisition unit is used to acquire historical pending information corresponding to the first historical time period and current pending information corresponding to the current time period from the data source.

[0181] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as Field Programmable Gate Arrays (FPGAs), Programmable Logic Arrays (PLAs), Systems-on-Chip, Systems-on-Substrate, Systems-on-Package, Application-Specific Integrated Circuits (ASICs), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0182] For example, any plurality of the acquisition module 910, the first determination module 920, the second determination module 930, and the third determination module 940 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the acquisition module 910, the first determination module 920, the second determination module 930, and the third determination module 940 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the acquisition module 910, the first determination module 920, the second determination module 930, and the third determination module 940 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0183] It should be noted that the resource configuration device part in the embodiments of this disclosure corresponds to the resource configuration method part in the embodiments of this disclosure. For a detailed description of the resource configuration device part, please refer to the resource configuration method part, which will not be repeated here.

[0184] Figure 10 A block diagram of an electronic device suitable for implementing a resource allocation method according to an embodiment of the present disclosure is shown schematically. Figure 10 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0185] like Figure 10 As shown, a computer electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage portion 1009 into a random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0186] RAM 1003 stores various programs and data required for the operation of electronic device 1000. Processor 1001, ROM 1002, and RAM 1003 are interconnected via bus 1004. Processor 1001 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 1002 and / or RAM 1003. It should be noted that the programs may also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0187] According to embodiments of this disclosure, the electronic device 1000 may further include an input / output (I / O) interface 1005, which is also connected to a bus 1004. The electronic device 1000 may also include one or more of the following components connected to the input / output (I / O) interface 1005: an input section 1006 including a keyboard, mouse, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the input / output (I / O) interface 1005 as needed. A removable medium 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1010 as needed so that computer programs read from it can be installed into the storage section 1008 as needed.

[0188] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1009, and / or installed from removable medium 1011. When the computer program is executed by processor 1001, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0189] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0190] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0191] For example, according to embodiments of this disclosure, a computer-readable storage medium may include the ROM 1002 and / or RAM 1003 described above and / or one or more memories other than ROM 1002 and RAM 1003.

[0192] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the resource configuration methods provided in the embodiments of this disclosure.

[0193] When the computer program is executed by the processor 1001, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0194] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 1009, and / or installed from a removable medium 1011. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0195] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0196] The flowcharts and block diagrams in the accompanying drawings 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 a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features recited in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not expressly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0197] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A resource allocation method, comprising: In response to receiving a resource configuration request, based on the current system time indicated by the resource configuration request, pending information and historical order information are obtained. The resource configuration request also includes the type of resource to be configured. The pending information includes current pending information corresponding to the current time period and historical pending information corresponding to a first historical time period. The current time period and the first historical time period are determined based on the current system time. Based on the current pending information and the historical pending information, M influence coefficients and corresponding influence variables are determined. The current pending information includes current coefficient information, and the historical pending information includes historical coefficient information and historical variable information. The influence coefficients are determined by: the ratio between the current coefficient information and the corresponding historical coefficient information; or by determining the current system time. The influence variables are determined based on the historical variable information and the corresponding influence coefficients, where M is a positive integer. Based on the historical order information, the M influence coefficients, and the influence variables corresponding to each of the M influence coefficients, predicted order information is determined. The predicted order information is determined based on a cumulative value and the historical order information. The cumulative value is obtained by summing the product values ​​corresponding to each influence coefficient, and the product value is the product between the influence coefficient and the influence variable corresponding to the influence coefficient. Based on the predicted order information, determine the resource configuration information corresponding to the resource type to be configured.

2. The method according to claim 1, wherein, The current information to be processed includes at least the first current coefficient information and the second current coefficient information, and the historical information to be processed includes at least the first historical coefficient information and the second historical coefficient information; The step of determining M influence coefficients and corresponding influence variables based on the current pending information and the historical pending information includes: The first ratio is determined as the first influence coefficient, wherein the first ratio is determined based on the first current coefficient information and the first historical coefficient information; The second ratio is determined as the second influence coefficient, wherein the second ratio is determined based on the second current coefficient information and the second historical coefficient information; Based on the current system time, determine the third influence coefficient; and Based on the historical variable information, determine the influencing variables corresponding to the first influence coefficient, the second influence coefficient, and the third influence coefficient, respectively.

3. The method according to claim 1, wherein, The historical order information includes actual historical order information and predicted historical order information corresponding to each of the N sub-historical time periods, where N is a positive integer; The method further includes, before determining the predicted order information based on the historical order information, the M influence coefficients, and the influence variables corresponding to each of the M influence coefficients: For each of the N sub-historical time periods, A first difference is determined based on the actual historical order information and the predicted historical order information corresponding to the sub-historical time period; Based on the actual historical order information and the first difference, a second difference is determined; Based on the second difference, determine the first product value corresponding to the sub-historical period; as well as The error assessment value is determined based on the first product value corresponding to each of the N sub-historical periods.

4. The method according to claim 3, wherein, The step of determining the predicted order information based on the historical order information, the M influence coefficients, and the influence variables corresponding to each of the M influence coefficients includes: For each of the M influence coefficients, Based on the influence coefficient and the influence variable corresponding to the influence coefficient, determine the second product value corresponding to the influence coefficient; The first cumulative value is determined based on the second product value corresponding to each of the M influence coefficients; Based on the historical order information and the first accumulated value, determine the second accumulated value; and The predicted order information is determined based on the second accumulated value and the error assessment value.

5. The method according to any one of claims 1 to 4, wherein, When the resource type to be configured is the first resource type, The step of determining the resource configuration information corresponding to the resource type to be configured based on the predicted order information includes: Based on the first resource type, obtain historical pending information corresponding to the second historical time period, wherein the historical pending information includes the number of historical objects and the number of historical resources; The third ratio is determined based on the number of historical objects and the number of historical resources; Based on the predicted order information and the third ratio, a fourth ratio is determined; and Based on the fourth ratio, the resource configuration information corresponding to the first resource type is determined.

6. The method according to claim 5, wherein, When the resource type to be configured is the second resource type, The step of determining the resource configuration information corresponding to the resource type to be configured based on the predicted order information includes: The predicted order information is filtered to obtain the predicted sub-order information corresponding to the second resource type; Based on the predicted sub-order information and the predetermined value, determine the fifth ratio; and Based on the fifth ratio, the resource configuration information corresponding to the second resource type is determined.

7. The method according to any one of claims 1 to 4, further comprising, after determining the resource configuration information corresponding to the resource type to be configured based on the predicted order information: Based on the type of resource to be configured, determine the predetermined resource configuration threshold corresponding to the type of resource to be configured; and If the relationship between the predetermined resource configuration threshold and the predicted resource configuration information does not meet the predetermined conditions, an early warning message is output.

8. The method according to any one of claims 1 to 4, wherein, The step of responding to a received resource configuration request and obtaining pending information and historical order information based on the current system time indicated by the resource configuration request includes: In response to receiving the resource configuration request, determine the historical system time corresponding to the current system time; The first historical time period is determined based on the first predetermined start time and the historical system time. The current time period is determined based on the second predetermined start time and the current system time; and Obtain the historical pending information corresponding to the first historical time period and the current pending information corresponding to the current time period from the data source.

9. A resource allocation device, comprising: The acquisition module is used to respond to receiving a resource configuration request and acquire pending information and historical order information according to the current system time indicated by the resource configuration request. The resource configuration request also includes the type of resource to be configured. The pending information includes current pending information corresponding to the current time period and historical pending information corresponding to a first historical time period. The current time period and the first historical time period are determined according to the current system time. The first determining module is used to determine M influence coefficients and corresponding influence variables based on the current information to be processed and the historical information to be processed. The current information to be processed includes current coefficient information, and the historical information to be processed includes historical coefficient information and historical variable information. The influence coefficients are determined by: the ratio between the current coefficient information and the corresponding historical coefficient information; or based on the current system time. The influence variables are determined based on the historical variable information and the corresponding influence coefficients, where M is a positive integer. The second determining module is used to determine predicted order information based on the historical order information, the M influence coefficients, and the influence variables corresponding to each of the M influence coefficients. The predicted order information is determined based on a cumulative value and the historical order information. The cumulative value is obtained by summing the product values ​​corresponding to each influence coefficient, and the product value is the product between the influence coefficient and the influence variable corresponding to the influence coefficient. The third determining module is used to determine the resource configuration information corresponding to the type of resource to be configured based on the predicted order information.

10. An electronic device, comprising: One or more processors; Memory, used to store one or more instructions. When the one or more instructions are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method of any one of claims 1 to 8.

11. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 8.

12. A computer program product comprising computer-executable instructions, which, when executed, are used to implement the method of any one of claims 1 to 8.

Images