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Enterprise field supplier recommending method based on BP neural network

A technology of BP neural network and recommendation method, applied in the field of data analysis and data mining, can solve the problems of increasing subjectivity of training set, insufficient objective and reliable results, and difficulty in obtaining the total score of suppliers.

Inactive Publication Date: 2017-03-15
ANSTEEL GRP MINING CO LTD
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AI Technical Summary

Problems solved by technology

Jiang Zhijuan proposed a method of using neural network to score suppliers in "Research on Supplier Evaluation and Selection Based on BP Neural Network and Cooperative Game". The training set itself increases subjectivity, making the predicted results not objective and reliable enough

Method used

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  • Enterprise field supplier recommending method based on BP neural network
  • Enterprise field supplier recommending method based on BP neural network
  • Enterprise field supplier recommending method based on BP neural network

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Embodiment Construction

[0041] An embodiment of the present invention will be further described below in conjunction with the accompanying drawings.

[0042] In the embodiment of the present invention, combined with the BP neural network supplier recommendation method in the enterprise field, the method flow chart is as follows figure 1 shown. Include the following steps:

[0043] Step 1. Determine supplier indicators and establish a supplier evaluation model;

[0044] In the embodiment of the present invention, the first-level indicators of suppliers: suppliers and bidding products; the second-level indicators of suppliers: credit, loyalty, basic information, satisfaction, bidding information and quality;

[0045] Supplier three-level indicators:

[0046] Credit: Whether there is a business license, whether the tax registration information is normal, annual sales performance, corporate credit rating, quality management system certification level, ISO system certification and registered capital; ...

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Abstract

The invention proposes an enterprise field supplier recommending method based on a BP neural network, and belongs to the technical field of data analysis and data mining. A neural network and a supplier index system can be updated with the increase of bidding data, which ensures the effectiveness of decisions and the change of trend. The method overcomes the difficulties as follows: the total score of a supplier is not easy to get, and the data set for prediction is not real and objective enough as suppliers are graded by means of direct introduction for a general method. The method is combined with the actual situation. The prediction results of the index system and a neural network model are fully fused, and a decision space is set aside for experts. It is thus ensured that supplier selection can be both subjective and objective. The supplier index system built in the invention starts from both suppliers and supplied products. The index capacity is expanded. The degree of preference to suppliers is considered. A more comprehensive and applicable index system is formed.

Description

technical field [0001] The invention relates to the technical field of data analysis and data mining, in particular to a method for recommending suppliers in the enterprise field combined with a BP neural network. Background technique [0002] At present, in the bidding process of mining companies, when mining companies first look for suppliers, they often rely on the personal experience of buyers to search for relevant information from the Internet, or choose suppliers subjectively due to interests. Therefore, inappropriate suppliers are often selected, and the process of selecting suppliers takes a long time, resulting in an increase in the cost of the enterprise. In addition, due to the many types of materials purchased by the enterprise and the frequent purchases, it is not suitable for the time-consuming and costly bidding process. In addition, mining companies tend to pay more attention to quality issues when purchasing professional equipment, so they will be more inc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q50/02G06N3/02
CPCG06Q30/0201G06N3/02G06Q50/02
Inventor 王欢付薇薇祁金才姜超孙为平肖成勇
Owner ANSTEEL GRP MINING CO LTD
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