Feature Selection for Vibration Signal Based on Rough Set and MMAS

摘要：

On the basis of dilation matrix, a new attribute reduction algorithm is put forward by applying the max-min ant system(MMAS) algorithm to finding reductions. Aiming at the problem of feature selection based on rough set theory, a comprehensive evaluation index is defined to evaluate the generalization capability and dimension of reductions. The reduction with the minimal index is regarded as the optimal feature subset, which can achieve the best compromise between generalization and dimension. By applying the algorithm to vibration signal, it is proved.

关键词： Rough Set MMAS Vibration Signal Feature Selection

作者: Sun Tao Hou Zhiqiang Wang Yonghua Jiang Keyi

作者单位: Naval Aeronautical and Astronautical University, Yantai, Shandong, 264001, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 1475-1478

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）