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A clustering Method of chinese medicine prescriptions Based on Modified firefly algorithm

chinese Journal of Integrative medicine 2016年第12期22卷 941-946页

作者：袁锋刘弘陈守强徐亮 School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Shandong Normal University School of Information Engineering Shandong Management University Heart Center Second Hospital Affiliated to Shandong University of Traditional Chinese Medicine School of Traditional Chinese Medicine Shandong University of Traditional Chinese Medicine

This paper is aimed to study the clustering method for chinese medicine（CM） medical cases. The traditional K-means clustering algorithm had shortcomings such as dependence of results on the selection of initial value, trapping in local optimum when processing prescriptions form CM medical cases. Therefore, a new clustering method based on the collaboration of firefly algorithm and simulated annealing algorithm was proposed. This algorithm dynamically determined the iteration of firefly algorithm and simulates sampling of annealing algorithm by fitness changes, and increased the diversity of swarm through expansion of the scope of the sudden jump, thereby effectively avoiding premature problem. The results from confirmatory experiments for CM medical cases suggested that, comparing with traditional K-means clustering algorithms, this method was greatly improved in the individual diversity and the obtained clustering results, the computing results from this method had a certain reference value for cluster analysis on CM prescriptions.

关键词： clustering firefly algorithm simulated annealing algorithm chinese medicine prescriptions

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