Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Enterprise pre-cooperative partner classification method based on SVM (support vector machine)

A technology of support vector machine and classification method is applied in the field of enterprise pre-partner classification based on support vector machine, which can solve the problems of lack of efficient and scientific enterprise pre-partner classification tools, and inability to provide scientific basis for enterprise partner decision-making.

Inactive Publication Date: 2016-08-17
DALIAN UNIV OF TECH
View PDF0 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention mainly solves the technical problem that in the prior art, manual screening of enterprise pre-partners is used, but an efficient and scientific enterprise pre-partner classification tool is lacking, and a scientific basis cannot be provided for the decision-making of enterprise partners, and a support vector machine-based approach is proposed. Enterprise pre-partner classification method, in order to achieve intelligent auxiliary decision-making for enterprise partner decision-making problems, and provide beneficial decision support for decision-makers

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Enterprise pre-cooperative partner classification method based on SVM (support vector machine)
  • Enterprise pre-cooperative partner classification method based on SVM (support vector machine)
  • Enterprise pre-cooperative partner classification method based on SVM (support vector machine)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] In order to make the technical problems solved by the present invention, the technical solutions adopted and the technical effects achieved clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention. In addition, it should be noted that, for the convenience of description, only parts related to the present invention are shown in the drawings but not all content.

[0042] figure 1 It is a flow chart of realizing the enterprise pre-partner classification method based on the support vector machine provided by the present invention. figure 2 It is a schematic diagram of the enterprise pre-partner classification method based on the support vector machine provided by the present invention. Such as figure 1 , 2 As shown, the support vector mac...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of mode recognition, and provides an enterprise pre-cooperative partner classification method based on an SVM (support vector machine). The method comprises the steps: 100, building a sample set; 200, building a classifier for enterprise pre-cooperative partners; 300, carrying out the training of the classifier for the enterprise pre-cooperative partners through a trained sample; 400, carrying out the performance assessment of the trained classifier for the enterprise pre-cooperative partners through employing a test sample; 500, carrying out the classification of the data of the enterprise pre-cooperative partners through the trained classifier for the enterprise pre-cooperative partners. The method is simple in implementation, is especially suitable to be used for judging whether a candidate partner is suitable for cooperation or not in enterprise information, can effectively reduce the manual decision-making time, and improves the decision-making intelligentization.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a support vector machine-based enterprise pre-partner classification method. Background technique [0002] At present, partners are a strategy to help companies increase their competitiveness in the global market. Lack of evaluation of partners is the main reason for cooperation failure. Since there are many factors that affect partner selection, they are interrelated and restrict each other, making it possible to judge whether a partner is suitable for cooperation needs. Do a lot of calculations. At the same time, in the partner search stage, the number of partners obtained through the search tool may be very large, and it is impossible to completely screen them manually. Therefore, it is very necessary to consider using computers as an auxiliary tool to carry out necessary intelligent auxiliary decision-making for business partner decision-making problems. , so as ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/06G06K9/62
CPCG06Q10/06375G06Q10/067G06F18/2411
Inventor 梁冰
Owner DALIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products