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Supplier default risk prediction method

A risk prediction and supplier technology, applied in the field of supplier default risk prediction, can solve problems such as lack of research and single data dimension, and achieve the effect of ensuring safe operation and reducing business risk

Pending Publication Date: 2021-11-12
OCEAN UNIV OF CHINA
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Problems solved by technology

[0006] In view of the lack of research on supplier default risk prediction in the current manufacturing industry and the single data dimension, this invention proposes a supplier default risk prediction method based on knowledge graphs and RLSTM algorithm technology to improve the stability of the enterprise supply chain system. Judge the risk of supplier default as soon as possible, and the technical effect of reducing the economic and time loss of the enterprise

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Embodiment Construction

[0020] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0021] The present invention aims to propose a supplier default risk prediction method, based on the five principles of the risk index system, combined with the characteristics of the manufacturing industry, to systematically analyze the factors that affect the supplier default risk of manufacturing enterprises, and use related indicators to Quantification of influencing factors. Aiming at problems such as supplier default in manufacturing enterprises, the RLSTM neural network structure is used to predict the risk of supplier default, and the supplier information is integrated into the supplier knowledge map, and the knowledge map link prediction technology is used to predict the supplier knowledge map. Completion, the information of related suppliers of adjacent parts is input into the RLSTM model through shaping, and t...

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Abstract

The invention discloses a supplier default risk prediction method. The supplier default risk prediction method provided by the invention comprises the following steps: constructing a supplier knowledge graph by using a knowledge graph technology, restoring partial missing information in the knowledge graph with time sequence characteristics by using a knowledge graph prediction link technology, comprehensively considering cross-domain data, and predicting the supplier default risk by adopting the neural network. Compared with a single-domain data prediction mode using historical sales volume or user feedback evaluation and the like in traditional supplier default risk prediction, the supplier supply risk in the prediction period can be effectively judged, and the method is helpful for analyzing the selection of future suppliers and ensuring the safe operation of a supply chain, and reduces the operation risk of an enterprise.

Description

technical field [0001] The invention belongs to the technical field of manufacturing supply chain management, and in particular relates to a supplier default risk prediction method. Background technique [0002] Compared with other industries, manufacturing and assembly procedures are numerous and complex, and a single enterprise cannot perform all the work. At present, most manufacturing enterprises outsource their non-core business and manufacture by purchasing parts. Parts suppliers have more and more initiative and technical power, so in an increasingly competitive environment, improving supply chain efficiency is a business strategy for companies to achieve rapid development. As the front link of the supply chain, the supplier plays a very important role in the supply chain. The interruption or suspension of any link in the industrial supply chain may cause the entire supply chain to stop. Scientific management of the supply chain is a key factor for enterprises to ach...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06F16/36G06N3/04G06N3/08G06Q50/04
CPCG06Q10/0635G06F16/367G06Q50/04G06N3/04G06N3/08Y02P90/30
Inventor 于树松高小燕郭保琪杨宁丁香乾石硕侯瑞春宫会丽
Owner OCEAN UNIV OF CHINA
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