Application of a New Association Rules Mining Algorithm in the Chinese Medical Coronary Disease

  • Feng Yuan
  • Hong Liu
  • ShouQiang Chen
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)


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.


Association rules mining Traditional chinese medicine Genetic algorithm Particle swarm optimization 


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.School of Information Science and EngineeringShandong Normal UniversityJinanChina
  2. 2.School of Information EngineeringCollege of Shandong Labour Union AdministratorsJinanChina
  3. 3.Center of Hear,The Second Affiliated Hospital of Shandong University of Traditional Chinese MedicineFujianChina

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