A Knowledge Context Fuzzy Clustering Method Based on Genetic Algorithm

摘要：

　　A fuzzy clustering method based on genetic algorithm is proposed aiming at the problem of automatic clustering of knowledge context.Firstly,the knowledge context model is constructed to determine the similarity measure of knowledge context.Then the initial clustering centers are obtained based on the density peak method.Then the fuzzy C mean clustering result is solved by genetic algorithm,and the clustering of knowledge context is realized.Finally,the knowledge context clustering of an aircraft part design process is taken as an example to illustrate the effectiveness of the algorithm.

作者: Faping Zhang Li Li Cuixiang Zhou

作者单位: School of Mechanical Engineering,Beijing Institute of Technology,Beijing,China No.208 Research Institute of China Ordnance Industries,Beijing,China

会议类型: 国际会议

会议名称: 2017第三届机械、电子和信息技术工程国际会议(ICMITE 2017)

会议地点: 成都

会议语种:英文

页码: 1-5

在线出版日期: 2017-12-16（万方平台首次上网日期，不代表论文的发表时间）