A clustering method of TCM prescriptions based on modified firefly algorithm

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Yuan Feng

Shandong University, China

: J Pharm Drug Deliv Res

Abstract

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This paper is aimed at studying the clustering for TCM 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 TCM medical cases, to overcome it, a new clustering method based on the collaboration of firefly algorithm and simulated annealing was proposed. This algorithm dynamically determines the iteration of firefly algorithm and simulates sampling of annealing algorithm by fitness changes, and increases the diversity of swarm through expansion of the scope of the sudden jump, thereby effectively avoiding premature problem. The results from confirmatory experiments for TCM 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 TCM prescriptions.

Biography

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Email: yuanfeng623@163.com