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CN-122022967-A - Auction risk prediction method, device, equipment and storage medium for idle waste resource disposal

CN122022967ACN 122022967 ACN122022967 ACN 122022967ACN-122022967-A

Abstract

The application discloses an auction risk prediction method, device, equipment and storage medium for idle waste material treatment, relating to the technical field of auction, wherein the method comprises the steps of obtaining basic attribute information and market environment information of target auction objects; and inputting the multidimensional risk factors into a pre-trained machine learning model, and outputting the default probability of object risk prediction of the target auction. The method can improve the prediction accuracy of the default probability.

Inventors

  • ZHOU JING
  • GUAN YUNLONG
  • LIU QIANGQIANG
  • HUANG HAO
  • LIU MING
  • XU XUEWEN
  • TIAN XIAOYUN
  • YAN BOBO
  • LIU SHIYUAN
  • YANG LIN
  • WANG YUAN
  • ZHANG BIN
  • HE XIN

Assignees

  • 国网电商科技有限公司
  • 东方电气集团(四川)物产有限公司

Dates

Publication Date
20260512
Application Date
20260130

Claims (10)

  1. 1. An auction risk prediction method for idle waste disposal, the method comprising: basic attribute information and market environment information of a target auction target object are acquired; calculating to obtain a multidimensional risk factor according to the basic attribute information and the market environment information; And inputting the multi-dimensional risk factors into a pre-trained machine learning model, and outputting the default probability of object risk prediction of the target auction.
  2. 2. The method according to claim 1, wherein the multi-dimensional risk factors include category risk factors, freshness and market heat index, and the calculating the multi-dimensional risk factors according to the basic attribute information and the market environment information includes: determining the material class of the target auction target object according to the basic attribute information; obtaining a category risk coefficient of the material category based on the historical average default rate and the basic risk coefficient of the material category; Obtaining the new rate of the target auction bidding object according to the service life, maintenance status score and appearance score of the materials contained in the basic attribute information; And obtaining the market heat index according to the historical performance rate of the current registering bidder in the market environment information.
  3. 3. The method according to claim 1, wherein the method further comprises: and calculating the deposit amount according to the default probability and the evaluation value of the auction bidding materials.
  4. 4. A method according to claim 3, wherein said calculating an amount of a deposit based on said probability of breach and a rating of said auction subject matter comprises: determining a guarantee gold regulating coefficient according to the default probability; multiplying the evaluation value of the auction subject by the Jin Diaojie coefficients of the guarantee to obtain the amount of the guarantee.
  5. 5. The method of claim 2, wherein the historical average odds ratio and base risk factor based on the category of the material, obtaining a category risk coefficient of the material category, comprising: Wherein, the Expressed in time Is the first of (2) Class risk coefficient of class materials, Represent the first Basic risk factors of the class of the goods, Representing the risk sensitivity adjustment parameter(s), Represent the first Historical average default rates for class of class material, Representing the historical average offence rate of all classes of the whole platform.
  6. 6. The method according to claim 2, wherein the obtaining the update rate of the target auction target object according to the service life, the maintenance status score, and the appearance score of the material included in the basic attribute information comprises: Wherein, the The new rate is indicated as the new rate, The service life of the materials is indicated, Representing the standard maximum service life of the material, Represents a maintenance condition score that is indicative of the maintenance condition, The appearance score is indicated and is displayed, A first weight is indicated and a second weight is indicated, A second weight is indicated as being indicative of a second weight, Representing a third weight.
  7. 7. The method of claim 2, wherein the obtaining the market heat index based on the historical performance rate of the currently registered bidder in the market environment information comprises: Wherein, the Expressed in time Is a combination of the heat index of the market, Indicating the cumulative number of registered persons of the current subject matter, Represent the first Historical performance rates of individual entry bidders, Representing the maximum of the historical performance rates of all bidders in the system, The time-decay factor is represented as such, Represent the first The time of entry of the bidding person, Represents the average number of registered persons of similar historical targets, Representing market benchmark adjustment factors.
  8. 8. An auction risk prediction device for idle waste disposal, the device comprising: the acquisition module is used for acquiring basic attribute information and market environment information of the target auction bidding materials; The processing module is used for calculating and obtaining a multidimensional risk factor according to the basic attribute information and the market environment information; And the prediction module is used for inputting the multi-dimensional risk factors into a pre-trained machine learning model and outputting the default probability of object risk prediction of the target auction.
  9. 9. A computing device comprising a memory and a processor; wherein one or more computer programs are stored in the memory, the one or more computer programs comprising instructions, which when executed by the processor, cause the computing device to perform the method of any of claims 1-7.
  10. 10. A computer-readable storage medium, characterized in that the computer-readable storage medium is for storing a computer program, the computer program is for performing the method of any of claims 1 to 7.

Description

Auction risk prediction method, device, equipment and storage medium for idle waste resource disposal Technical Field The application relates to the technical field of auction, in particular to an auction risk prediction method, an auction risk prediction device, auction risk prediction equipment and an auction risk prediction storage medium for idle waste material treatment. Background In order to ensure the seriousness of the auction process and prevent the risks of malicious bidding or default after the bidding of bidders, an auction guarantee system is an indispensable core wind control link in the platform. Essentially, the deposit is set to cover the potential loss of default, and the reasonable amount is mainly determined by two factors, namely, the value (evaluation value) of the bidding object itself, which is the basis of loss compensation, and the predicted value (default probability predicted value) of the potential default of the bidding person in the transaction, which is the quantitative estimation of the risk occurrence probability. At present, the auction deposit calculation method commonly adopted in the industry mainly comprises a fixed proportion method, namely, calculating deposit according to a preset unified proportion (such as 10%) according to the evaluation value of a target object, wherein the method is simple to realize but lacks flexibility, and a manual experience method, namely, an operator manually sets fixed amount according to subjective judgment of the type of the material, market conditions and the like, and the method has certain pertinence, but is low in efficiency and difficult to be applied in a standardized and large-scale mode. However, prior art solutions do not accurately predict the risk of an auction system, i.e. the probability of a breach. Disclosure of Invention The application provides an auction risk prediction method, device, equipment and storage medium for idle waste material treatment, which can improve the prediction accuracy of default probability. In order to achieve the above purpose, the application adopts the following technical scheme: In a first aspect, the present application provides an auction risk prediction method for idle waste disposal, comprising: basic attribute information and market environment information of a target auction target object are acquired; calculating to obtain a multidimensional risk factor according to the basic attribute information and the market environment information; And inputting the multi-dimensional risk factors into a pre-trained machine learning model, and outputting the default probability of object risk prediction of the target auction. Optionally, the multi-dimensional risk factor includes a category risk factor, a freshness and a market heat index, and the calculating to obtain the multi-dimensional risk factor according to the basic attribute information and the market environment information includes: determining the material class of the target auction target object according to the basic attribute information; obtaining a category risk coefficient of the material category based on the historical average default rate and the basic risk coefficient of the material category; Obtaining the new rate of the target auction bidding object according to the service life, maintenance status score and appearance score of the materials contained in the basic attribute information; And obtaining the market heat index according to the historical performance rate of the current registering bidder in the market environment information. Optionally, the method further comprises: and calculating the deposit amount according to the default probability and the evaluation value of the auction bidding materials. Optionally, the calculating the deposit amount according to the breach probability and the evaluation of the auction bid object includes: determining a guarantee gold regulating coefficient according to the default probability; multiplying the evaluation value of the auction subject by the Jin Diaojie coefficients of the guarantee to obtain the amount of the guarantee. Optionally, the obtaining the class risk coefficient of the material class based on the historical average default rate and the basic risk coefficient of the material class includes: Wherein, the Expressed in timeIs the first of (2)Class risk coefficient of class materials,Represent the firstBasic risk factors of the class of the goods,Representing the risk sensitivity adjustment parameter(s),Represent the firstHistorical average default rates for class of class material,Representing the historical average offence rate of all classes of the whole platform. Optionally, the obtaining the new rate of the target auction target object according to the service life, the maintenance status score and the appearance score of the materials contained in the basic attribute information includes: Wherein, the The new rate is indicated as the new rate,The service