Knowledge Mining of Traditional Chinese Medicine Constitution Classification Rules Based on Artificial Fish School Algorithm

摘要：

Human Constitution is a complex multi-factor, and is difficult to get accurate results using TCM (Traditional Chinese Medicine) Constitution classification and criterion. AFSA (Artificial Fish School Algorithm) is an optimization algorithm based on biological models. The coding scheme of the Classification rule is designed by using AFSA, the more accurate Classification Rule Model is constructed by learning the upper and lower boundaries of continuous attributes and putting forward a new fitness function of Classification Rule. The experiment shows that it can get concise and easily understandable rule set by using the miningalgorithm based on ASF A, and the accuracy of mining results on rule set is higher.

关键词： AFSA Knowledge Mining Training Sets Feature Attribute TCM Constitution Classification

作者: Feng Yang Guoliang Tang Hemin Jin

作者单位: Institute of Information Technology, Henan University of TCM Zhengzhou, Henan, 450008, China Library,Henan University of TCM Zhengzhou, Henan, 450008, China

会议类型: 国际会议

会议名称: 2011 IEEE 3rd International Conference on Communication Software and Networks(2011第三届通信软件与网络国际会议 ICCSN2011)

会议地点: 西安

会议语种:英文

页码: 462-466

在线出版日期: 2011-05-27（万方平台首次上网日期，不代表论文的发表时间）