Study on Classification Model Based on Relevance Vector Machine with Genetic Algorithm

摘要：

A novel classification method based on relevance vector machine with genetic algorithm is presented in the paper.In the model,genetic algorithm is applied to gain the suitable training parameters of relevance vector machine.State classification of roll bearing is applied to testify the classification ability of the proposed method,and state classification data of roll bearing are given.The experimental results show that relevance vector machine with genetic algorithm has higher classification accuracy than backpropagation neural network and support vector machine.

关键词： relevance vector machine classification model genetic algorithm Bayesian

作者: Yanhong Li Taihui Liu

作者单位: Mathematical College Bcihua University Jilin 132013 China Computer College Bcihua University Jilin 132013 China

会议类型: 国际会议

会议名称: 2010 2nd IEEE International Conference on Information and Financial Engineering(2010年第二届IEEE信息与金融工程国际会议 ICIFE 2010)

会议地点: 重庆

会议语种:英文

页码: 538-541

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）