Text Knowledge Acquisition Method of Collaborative Product Design Based on Genetic Algorithm

Author:

Li Chongyuan1ORCID,Yang Mengmeng12

Affiliation:

1. Haikou University of Economics, Haikou, Hainan 570000, China

2. HaiNan Normal University, Hainan 570000, China

Abstract

In order to overcome the problems of poor clustering effect and large error of text knowledge acquisition in traditional text knowledge acquisition methods, a new text knowledge acquisition method of collaborative product design based on genetic algorithm is proposed in this paper. The definition of collaborative product design text knowledge clustering is given. According to the operation process of the genetic algorithm, the chromosomes of clustered text are constructed and encoded and the initial population is obtained. The fitness function of clustering is constructed by the DB index evaluation method; the selection, crossover, and mutation operators in the genetic algorithm are determined; and the objective function of collaborative product design text knowledge clustering is constructed. After the text knowledge clustering is completed, the text knowledge data of collaborative product design are obtained in an all-around way by using the method of rough set and neural network. The experimental results show that compared with the traditional text knowledge acquisition methods, the clustering effect of the proposed method is better and the text knowledge error is reduced up to 0.02.

Funder

Hainan Characteristic Tourism Commodity

Publisher

Hindawi Limited

Subject

General Mathematics

Reference22 articles.

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