标题：Application of a new association rules mining algorithm in the Chinese medical coronary disease
作者：Yuan, Feng ;Liu, Hong ;Chen, ShouQiang
作者机构：[Yuan, Feng ;Liu, Hong ] School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China;[Chen, ShouQiang ] Center of H 更多
会议名称：5th International Symposium on IT in Medicine and Education, ITME 2013
会议日期：July 19, 2013 - July 21, 2013
来源：Lecture Notes in Electrical Engineering
摘要：The paper deals with efficient mining association rules in large data sets of TCM clinical data of the coronary disease. Aiming at the problems that TCM clinical data exist a great deal of data and high association characteristics, which lead to the problem of low efficiency, slow convergence and omission rules, a new combined method is proposed based on genetic algorithm and particle swarm optimization. The method designs the fitness function, uses particle swarm optimization to finish evolution and integration, and combines with genetic manipulation the advantage of simple and robust. The medical treatment records of coronary disease were verified by the experiments. Experimental results show that compared with traditional association rules mining method, combined algorithm performs better in terms of diversity of population and discovering more effective association rules. The mining result has reference value in TCM treatment of the coronary disease. © Springer Science+Business Media Dordrecht 2014.