一種基于CSA的模糊聚類新算法
A CSA-Based New Fuzzy Clustering Algorithm
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摘要: 在聚類分析中,模糊k均值算法是目前應(yīng)用最為廣泛的方法之一,然而該算法對(duì)初始化敏感,容易陷入局部極值點(diǎn)。為此,該文提出一種基于克隆選擇的模糊聚類新算法以實(shí)現(xiàn)全局優(yōu)化處理。在新算法中,由于克隆算子能夠?qū)⑦M(jìn)化搜索與隨機(jī)搜索、全局搜索和局部搜索相結(jié)合,因而通過(guò)對(duì)候選解進(jìn)行克隆算子操作,能夠快速得到全局最優(yōu)解。用人造數(shù)據(jù)和IRIS實(shí)際數(shù)據(jù)所做測(cè)試結(jié)果表明了新算法的有效性。
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關(guān)鍵詞:
- 聚類分析; 克隆選擇算法; 模糊k均值算法; 遺傳算法
Abstract: In cluster analysis, Fuzzy K-Means (FKM) algorithm is one of the most widely used methods. However, FKM algorithm is much more sensitive to the initialization, and easy to fall into local optimum. For this purpose, this paper presents a clonal selection based new algorithm for fuzzy clustering analysis, for global optimization. Since the clonal operator can combine the evolutionary search and random search, and incorporate the global search with local search, by the clonal operation on candidate solutions, the new algorithm can quickly obtain the global optimum. The experimental results with synthetic data and IRIS real data illustrate the effectiveness of the new algorithm. -
何清.模糊聚類分析理論與應(yīng)用研究進(jìn)展.模糊系統(tǒng)與數(shù)學(xué),1998,12(2):89-94.[2]高新波.模糊聚類算法的優(yōu)化及應(yīng)用研究.[博士論文],西安:西安電子科技大學(xué),1999年.[3]De Castro L N.[J].Von Zuben F J. The clonal selection algorithm with engineering applications. Proc. of GECCO00, Workshop on Artificial Immune Systems and Their Applications, Las Vegas,USA.2000,:-[4]Kim Jungwon, Bentley P J. Towards an artificial immune system for network intrusion detection: An investigation of clonal selection with a negative selection operator. Proc. of the 2001Congress on Evolutionary Computation, Seoul, Korea, 2001, 2:1244- 1252.[5]Du Haifeng, Jiao Licheng. Clonal operator and antibody clonal algorithm. Proc. of the First International Conference on Machine Learning and Cybernetics, Beijing, 4 - 5 Novermber, 2002:506-510.[6]周光炎.免疫學(xué)原理.上海:上?？茖W(xué)技術(shù)出版社,2000:31-32. -
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