CN113570124A - Object assignment method and device and electronic equipment - Google Patents

Object assignment method and device and electronic equipment Download PDF

Info

Publication number
CN113570124A
CN113570124A CN202110799206.5A CN202110799206A CN113570124A CN 113570124 A CN113570124 A CN 113570124A CN 202110799206 A CN202110799206 A CN 202110799206A CN 113570124 A CN113570124 A CN 113570124A
Authority
CN
China
Prior art keywords
recovered
performance data
recovery
recovery performance
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202110799206.5A
Other languages
Chinese (zh)
Inventor
沈赟
白苗君
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shanghai Qiyue Information Technology Co Ltd
Original Assignee
Shanghai Qiyue Information Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shanghai Qiyue Information Technology Co Ltd filed Critical Shanghai Qiyue Information Technology Co Ltd
Priority to CN202110799206.5A priority Critical patent/CN113570124A/en
Publication of CN113570124A publication Critical patent/CN113570124A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/30—Administration of product recycling or disposal
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
    • Y02W90/00—Enabling technologies or technologies with a potential or indirect contribution to greenhouse gas [GHG] emissions mitigation

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Operations Research (AREA)
  • Physics & Mathematics (AREA)
  • Marketing (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Entrepreneurship & Innovation (AREA)
  • General Business, Economics & Management (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Development Economics (AREA)
  • Game Theory and Decision Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The embodiment of the present specification provides an object assignment method, which includes obtaining recovery performance data of a recovered object, predicting recovery performance data of a to-be-recovered object based on the recovery performance data of the recovered object, and assigning an assignment to the to-be-recovered object based on the recovery performance data of the to-be-recovered object. By predicting the recovery performance data of the object to be recovered in advance by means of the recovery performance data of the recovered object and then assigning values, adaptive measures can be taken in advance before recovery, and the management and control level is improved.

Description

Object assignment method and device and electronic equipment
Technical Field
The application relates to the field of computers, in particular to an object assignment method and device and electronic equipment.
Background
Some virtual or physical objects may have changed in value or performance after a round of release to reclamation.
To manage these objects, the industry records or assesses their value and assigns values to the objects.
However, most of the current assignment methods are assignment after object recovery, and essentially belong to post-record, and such methods have poor control level and poor adaptability.
Disclosure of Invention
The embodiment of the specification provides an object assignment method and device and electronic equipment, and is used for improving the control level of an object.
An embodiment of the present specification further provides an object assignment method, including:
acquiring recovery performance data of a recovered object;
predicting the recovery expression data of the object to be recovered based on the recovery expression data of the recovered object;
and assigning the objects to be recovered based on the recovery performance data of the objects to be recovered.
Optionally, the predicting the recovery performance data of the object to be recovered based on the recovery performance data of the recovered object includes:
and fitting by using the recovery performance data, and predicting the recovery performance data of the object to be recovered by using the fitted function.
Optionally, the method further comprises:
and determining the attribute information of the object to be recovered, and correcting the predicted recovery performance data based on the attribute information of the object to be recovered.
Optionally, the attribute information includes: a volume of the object, a release time of the object, and a type of the object.
Optionally, the method further comprises:
the recovery expression data is decomposed into a plurality of mutually independent functions.
Optionally, the object is a recyclable asset.
Optionally, the method further comprises:
and generating a risk control strategy according to the assigned object to be recovered.
Optionally, the object is a memory for creating a storage space, and the recovery performance data is a storage performance parameter after the storage space is recovered.
Optionally, the method further comprises:
and generating a storage space scheduling strategy based on the object to be recovered after the value assignment.
An embodiment of the present specification further provides an apparatus for assigning an object, including:
the data acquisition module is used for acquiring recovery performance data of a recovered object;
the prediction module is used for predicting the recovery expression data of the object to be recovered based on the recovery expression data of the recovered object;
and the assignment module is used for assigning the objects to be recovered based on the recovery performance data of the objects to be recovered.
Optionally, the predicting the recovery performance data of the object to be recovered based on the recovery performance data of the recovered object includes:
and fitting by using the recovery performance data, and predicting the recovery performance data of the object to be recovered by using the fitted function.
Optionally, the method further comprises:
and determining the attribute information of the object to be recovered, and correcting the predicted recovery performance data based on the attribute information of the object to be recovered.
Optionally, the attribute information includes: a volume of the object, a release time of the object, and a type of the object.
Optionally, the method further comprises:
the recovery expression data is decomposed into a plurality of mutually independent functions.
Optionally, the object is a recyclable asset.
Optionally, the method further comprises:
and generating a risk control strategy according to the assigned object to be recovered.
Optionally, the object is a memory for creating a storage space, and the recovery performance data is a storage performance parameter after the storage space is recovered.
Optionally, the method further comprises:
and generating a storage space scheduling strategy based on the object to be recovered after the value assignment.
An embodiment of the present specification further provides an electronic device, where the electronic device includes:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform any of the methods described above.
The present specification also provides a computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement any of the above methods.
In various technical solutions provided in the embodiments of the present specification, recovery performance data of an object to be recovered is obtained, the recovery performance data of the object to be recovered is predicted based on the recovery performance data of the object to be recovered, and the object to be recovered is assigned based on the recovery performance data of the object to be recovered. By predicting the recovery performance data of the object to be recovered in advance by means of the recovery performance data of the recovered object and then assigning values, adaptive measures can be taken in advance before recovery, and the management and control level is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic diagram illustrating an object assignment method according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an object assignment device according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.
Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.
In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Fig. 1 is a schematic diagram of an object assignment method provided in an embodiment of the present disclosure, where the method may include:
s101: recovery performance data of the recovered object is acquired.
In real life, many virtual objects or physical objects are vigorous to go through a release-to-recycle process, in which the value of the objects is often lost, and therefore, the objects need to be assigned for management.
For example, in the embodiments of the present specification, the object is a recyclable asset.
This may mean, in practice, that the valuation of the recoverable asset may change and that the valuation may be redetermined upon recovery.
In particular, the recoverable asset may be an overdue owered asset.
For another example, the storage times of a storage medium often have a certain upper limit, and after each storage, the performance may be somewhat impaired, even if the impairment is less pronounced.
Therefore, before the storage space is recycled, if the future storage space value can be predicted, scientific planning and scheduling strategies can be made in advance.
In an embodiment of the present specification, the object is a memory for creating a memory space.
As another example, the object may be a product in a second-hand trading platform, such that the second-hand product may be valued in advance.
Of course, the recycle price can be evaluated at the first purchase to obtain the value-keeping rate, and whether to purchase the product can be judged according to the value-keeping rate.
S102: and predicting the recovery performance data of the object to be recovered based on the recovery performance data of the recovered object.
In an embodiment of this specification, the predicting, based on the recovery performance data of the recovered object, the recovery performance data of the object to be recovered may include:
and fitting by using the recovery performance data, and predicting the recovery performance data of the object to be recovered by using the fitted function.
In an embodiment of the present specification, the method may further include:
the recovery expression data is decomposed into a plurality of mutually independent functions.
Then, the independent function values are respectively predicted, and the recovery performance data is calculated according to the prediction result of each function.
Therefore, the interference among all the influencing factors can be reduced, and the prediction accuracy is improved.
S103: and assigning the objects to be recovered based on the recovery performance data of the objects to be recovered.
The method comprises the steps of obtaining recovery performance data of a recovered object, predicting the recovery performance data of a to-be-recovered object based on the recovery performance data of the recovered object, and assigning a value to the to-be-recovered object based on the recovery performance data of the to-be-recovered object. By predicting the recovery performance data of the object to be recovered in advance by means of the recovery performance data of the recovered object and then assigning values, adaptive measures can be taken in advance before recovery, and the management and control level is improved.
In the embodiment of this specification, still include:
and determining the attribute information of the object to be recovered, and correcting the predicted recovery performance data based on the attribute information of the object to be recovered.
In an embodiment of the present specification, the attribute information includes: a volume of the object, a release time of the object, and a type of the object.
In this embodiment, if the object is a recyclable asset, the method may further include:
and generating a risk control strategy according to the assigned object to be recovered.
In this embodiment, if the object is a memory used for creating a storage space, and the recovery performance data is a storage performance parameter after the storage space is recovered, the method may further include:
and generating a storage space scheduling strategy based on the object to be recovered after the value assignment.
In the field of internet financial credit, the last link of wind control is to dispose of the bad assets, wherein the most important is to reasonably price the bad assets, and the recovery condition of the assets in a future period is an important factor influencing the pricing, so the method is particularly important for predicting the recovery valuation.
The recovery performance data can refer to the recovery rate of overdue assets, and the recovery rate is influenced by the account age, the observation time and the overdue state entering time to a certain extent, so that the risk and the multidimensional change rule of the recovery rate can be comprehensively learned by a decomposition fitting method.
In specific implementation, the historical recovery rate data can be subjected to logarithmic conversion, and the converted recovery rate data can be disassembled into the superposition of three independent functions (an account age (m) function, an observation time (t) function and a function of entering a late month (v)).
The account age function represents the intrinsic risks of the passenger groups, the recovery level of the overdue month function representation overdue initial stage is entered, and the influence of the extrinsic risks of the external macroscopic environment on the recovery is observed.
And respectively fitting the three function curves in a step-by-step iteration mode, and predicting the recovery rate which does not occur. And (3) calculating the value of the account age (m) corresponding to the asset, the observed time (t) and the month (v) which enters the overdue state at the earliest time according to the predicted recovery rate, and predicting the future recovery performance.
The method comprises the steps of firstly obtaining latest overdue asset recovery data, then fitting the data by using a gradual iterative fitting method, predicting the future recovery rate based on a fitted function, classifying assets according to the overdue time of the bad assets, mapping the assets to the predicted recovery rate data, correcting the predicted recovery rate based on the packing time of the assets, and finally carrying out reasonable pricing on the assets by combining asset cost and asset types based on the predicted value of the recovery rate of the bad assets.
By the method, the recovery rate of the overdue assets can be accurately and automatically predicted and reasonable pricing can be completed based on the existing historical recovery data.
Fig. 2 is a schematic structural diagram of an object assignment device provided in an embodiment of this specification, where the device may include:
a data obtaining module 201, configured to obtain recovery performance data of a recovered object;
the prediction module 202 is configured to predict the recovery performance data of the object to be recovered based on the recovery performance data of the recovered object;
and the assignment module 203 is configured to assign a value to the object to be recovered based on the recovery performance data of the object to be recovered.
In an embodiment of this specification, the predicting recovery performance data of an object to be recovered based on recovery performance data of the object already recovered includes:
and fitting by using the recovery performance data, and predicting the recovery performance data of the object to be recovered by using the fitted function.
In the embodiment of this specification, still include:
and determining the attribute information of the object to be recovered, and correcting the predicted recovery performance data based on the attribute information of the object to be recovered.
In an embodiment of the present specification, the attribute information includes: a volume of the object, a release time of the object, and a type of the object.
In the embodiment of this specification, still include:
the recovery expression data is decomposed into a plurality of mutually independent functions.
In an embodiment of the present specification, the object is a recyclable asset.
In the embodiment of this specification, still include:
and generating a risk control strategy according to the assigned object to be recovered.
In the embodiment of the present specification, the object is a memory used for creating a storage space, and the recovery performance data is a storage performance parameter after the storage space is recovered.
In the embodiment of this specification, still include:
and generating a storage space scheduling strategy based on the object to be recovered after the value assignment.
The device predicts the recovery performance data of the object to be recovered based on the recovery performance data of the recovered object by acquiring the recovery performance data of the recovered object, and assigns a value to the object to be recovered based on the recovery performance data of the object to be recovered. By predicting the recovery performance data of the object to be recovered in advance by means of the recovery performance data of the recovered object and then assigning values, adaptive measures can be taken in advance before recovery, and the management and control level is improved.
Based on the same inventive concept, the embodiment of the specification further provides the electronic equipment.
In the following, embodiments of the electronic device of the present invention are described, which may be regarded as specific physical implementations for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.
Fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure. An electronic device 300 according to this embodiment of the invention is described below with reference to fig. 3. The electronic device 300 shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 3, electronic device 300 is embodied in the form of a general purpose computing device. The components of electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one memory unit 320, a bus 330 connecting the various system components (including the memory unit 320 and the processing unit 310), a display unit 340, and the like.
Wherein the storage unit stores program code executable by the processing unit 310 to cause the processing unit 310 to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned processing method section of the present specification. For example, the processing unit 310 may perform the steps as shown in fig. 1.
The storage unit 320 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)3201 and/or a cache storage unit 3202, and may further include a read only memory unit (ROM) 3203.
The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
Bus 330 may be one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 300, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 300 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 350. Also, the electronic device 300 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 360. Network adapter 360 may communicate with other modules of electronic device 300 via bus 330. It should be appreciated that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAI D systems, tape drives, and data backup storage systems, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to implement the above-described method of the invention, namely: such as the method shown in fig. 1.
Fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
A computer program implementing the method shown in fig. 1 may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (12)

1. A method for assigning values to objects, comprising:
acquiring recovery performance data of a recovered object;
predicting the recovery expression data of the object to be recovered based on the recovery expression data of the recovered object;
and assigning the objects to be recovered based on the recovery performance data of the objects to be recovered.
2. The method according to claim 1, wherein predicting the recovery performance data of the object to be recovered based on the recovery performance data of the object to be recovered comprises:
and fitting by using the recovery performance data, and predicting the recovery performance data of the object to be recovered by using the fitted function.
3. The method according to any one of claims 1-2, further comprising:
and determining the attribute information of the object to be recovered, and correcting the predicted recovery performance data based on the attribute information of the object to be recovered.
4. The method according to any one of claims 1-3, wherein the attribute information comprises: a volume of the object, a release time of the object, and a type of the object.
5. The method according to any one of claims 1-3, further comprising:
the recovery expression data is decomposed into a plurality of mutually independent functions.
6. The method of any of claims 1-5, wherein the object is a recyclable asset.
7. The method according to any one of claims 1-6, further comprising:
and generating a risk control strategy according to the assigned object to be recovered.
8. The method according to any one of claims 1-7, wherein the object is a memory for creating a memory space, and the reclamation performance data is a memory performance parameter after reclamation of the memory space.
9. The method according to any one of claims 1-8, further comprising:
and generating a storage space scheduling strategy based on the object to be recovered after the value assignment.
10. An apparatus for assigning values to objects, comprising:
the data acquisition module is used for acquiring recovery performance data of a recovered object;
the prediction module is used for predicting the recovery expression data of the object to be recovered based on the recovery expression data of the recovered object;
and the assignment module is used for assigning the objects to be recovered based on the recovery performance data of the objects to be recovered.
11. An electronic device, wherein the electronic device comprises:
a processor; and the number of the first and second groups,
a memory storing a computer executable program that, when executed, causes the processor to perform the method of any of claims 1-9.
12. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 1-9.
CN202110799206.5A 2021-07-15 2021-07-15 Object assignment method and device and electronic equipment Pending CN113570124A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110799206.5A CN113570124A (en) 2021-07-15 2021-07-15 Object assignment method and device and electronic equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110799206.5A CN113570124A (en) 2021-07-15 2021-07-15 Object assignment method and device and electronic equipment

Publications (1)

Publication Number Publication Date
CN113570124A true CN113570124A (en) 2021-10-29

Family

ID=78164977

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110799206.5A Pending CN113570124A (en) 2021-07-15 2021-07-15 Object assignment method and device and electronic equipment

Country Status (1)

Country Link
CN (1) CN113570124A (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107133301A (en) * 2017-04-27 2017-09-05 北京小米移动软件有限公司 The Forecasting Methodology and device of probability
US20180121845A1 (en) * 2016-10-31 2018-05-03 International Business Machines Corporation System, method and computer program product for characterizing object status and determining a maintenance schedule
CN110659998A (en) * 2019-08-20 2020-01-07 中国平安人寿保险股份有限公司 Data processing method, data processing apparatus, computer apparatus, and storage medium
CN111950600A (en) * 2020-07-20 2020-11-17 上海淇馥信息技术有限公司 Method and device for predicting overdue user resource return performance and electronic equipment
CN111950770A (en) * 2020-07-20 2020-11-17 上海淇馥信息技术有限公司 Method and device for managing resource return auxiliary strategy and electronic equipment
CN112288163A (en) * 2020-10-29 2021-01-29 平安科技（深圳）有限公司 Target factor prediction method of target object and related equipment
CN112508692A (en) * 2021-02-04 2021-03-16 北京淇瑀信息科技有限公司 Resource recovery risk prediction method and device based on convolutional neural network and electronic equipment

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180121845A1 (en) * 2016-10-31 2018-05-03 International Business Machines Corporation System, method and computer program product for characterizing object status and determining a maintenance schedule
CN107133301A (en) * 2017-04-27 2017-09-05 北京小米移动软件有限公司 The Forecasting Methodology and device of probability
CN110659998A (en) * 2019-08-20 2020-01-07 中国平安人寿保险股份有限公司 Data processing method, data processing apparatus, computer apparatus, and storage medium
CN111950600A (en) * 2020-07-20 2020-11-17 上海淇馥信息技术有限公司 Method and device for predicting overdue user resource return performance and electronic equipment
CN111950770A (en) * 2020-07-20 2020-11-17 上海淇馥信息技术有限公司 Method and device for managing resource return auxiliary strategy and electronic equipment
CN112288163A (en) * 2020-10-29 2021-01-29 平安科技（深圳）有限公司 Target factor prediction method of target object and related equipment
CN112508692A (en) * 2021-02-04 2021-03-16 北京淇瑀信息科技有限公司 Resource recovery risk prediction method and device based on convolutional neural network and electronic equipment

Similar Documents

Publication Publication Date Title
CN112508723B (en) Financial risk prediction method and device based on automatic preferential modeling and electronic equipment
CN112488199B (en) Logistics distribution mode prediction method, system, equipment and storage medium
CN111191894A (en) Method and device for processing resource demand based on user classification and electronic equipment
CN112015402A (en) Method and device for quickly establishing service scene and electronic equipment
CN112381563A (en) Automatic label generation method and device and electronic equipment
US11860727B2 (en) Data quality-based computations for KPIs derived from time-series data
CN110363583B (en) Method and device for creating user consumption behavior label based on position information and electronic equipment
CN109544392B (en) Method, system, device and medium for insurance order processing
CN110689425A (en) Method and device for pricing quota based on income and electronic equipment
CN110766202A (en) Contract settlement system, method and equipment for predicting channel capacity
CN111353872A (en) Credit granting processing method and device based on financial performance value and electronic equipment
CN111681094B (en) Method and device for monitoring resource policy abnormality and electronic equipment
CN112488865A (en) Financial risk prediction method and device based on financial time nodes and electronic equipment
CN112508692A (en) Resource recovery risk prediction method and device based on convolutional neural network and electronic equipment
CN112288475A (en) Product recommendation method and device and electronic equipment
CN112312335A (en) Reminding short message sending method and device and electronic equipment
CN111582649A (en) Risk assessment method and device based on user APP unique hot coding and electronic equipment
CN113570124A (en) Object assignment method and device and electronic equipment
CN113850611B (en) Marketing task execution method and device based on response surface and electronic equipment
CN111681093B (en) Method and device for displaying resource page and electronic equipment
CN110019172A (en) Data processing method, device, storage medium and electronic equipment
CN113222493A (en) Supply chain inventory management method and device and electronic equipment
CN113157699A (en) Business data auditing method and device and electronic equipment
CN112419025A (en) User data processing method and device, storage medium and electronic equipment
CN111950770A (en) Method and device for managing resource return auxiliary strategy and electronic equipment

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination