计算机技术与发展Issue(10)：44-47,4.DOI:10.3969/j.issn.1673-629X.2013.10.011
粒子群与细菌觅食相结合的案例聚类算法
Case Clustering Algorithm Combining Particle Swarm Optimization and Bacterial Foraging
摘要
Abstract
Case clustering is classified by the similarity to cases in case-base,the object is to reduce the time for searching similar case, improve the performance of case-base system and reduce the complexity of maintaining the case-base. The difficulty problem lies in that the size of case base is very large,and the clustering results is influenced by the choice of the clustering algorithm. In this paper,combined the advantages of particle swarm algorithm and bacterial foraging algorithm,use in case clustering with k-prototypes. Compared with pop-ular clustering algorithm show that this algorithm is efficient,has better performance.关键词
案例库/粒子群算法/细菌觅食算法/k-prototypes算法Key words
case base/particle swarm optimization/bacterial foraging algorithm/k-prototypes algorithm分类
信息技术与安全科学引用本文复制引用
胡爱策,任明仑,王浩..粒子群与细菌觅食相结合的案例聚类算法[J].计算机技术与发展,2013,(10):44-47,4.基金项目
国家自然科学基金资助项目(71271073,70871032) （71271073,70871032）
教育部新世纪优秀人才支持计划(NCET-11-0625) （NCET-11-0625）
