Adaptive fuzzy clustering based on genetic algorithm

摘要：

Traditional Fuzzy c-means (FCM) algorithm Is commonly used in unsupervised learning. However, there are some limitations. Cluster number should be determined and the cluster center should be initialized before classification. A new algorithm is proposed in the paper. The best cluster number is obtained by analyzing cluster validity function and the cluster center is initialized by HCM. The data set is classified with Fuzzy c-means algorithm based on Genetic algorithm. The experimental results indicate the effectiveness and adaptability of the new algorithm.

关键词： Cluster Analysis Cluster validity Fuzzy C-means Genetic algorithm

作者: Zhu Lianjiang Qu Shouning Du Tao

作者单位: College of Information Science and Engineering University of Jinan Jinan,China Information Network Center University of Jinan Jinan,China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 79-82

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）