计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
3期
138-142
,共5页
K-均值%聚类分析%人工鱼群算法%免疫接种
K-均值%聚類分析%人工魚群算法%免疫接種
K-균치%취류분석%인공어군산법%면역접충
K-means%clustering analysis%artificial fish swarm algorithm%immunity-vaccination
传统的K-均值聚类方法,在聚类过程中过度依赖初始聚类中心的选择,同时由于全局搜索能力的不足,很难得到精确的聚类中心。鱼群算法在解决优化问题中表现出良好的并行性和全局搜索特性,但由于人为设置参数的影响可能会陷入局部最优。针对聚类问题的特征,将鱼群算法运用到聚类问题中,在使用自适应步长的鱼群算法的基础上,进一步融合免疫接种机制,加强算法对精确解的搜索性能,通过UCI数据集上的实验分析和比较,表明算法具有更好的有效性和稳定性。
傳統的K-均值聚類方法,在聚類過程中過度依賴初始聚類中心的選擇,同時由于全跼搜索能力的不足,很難得到精確的聚類中心。魚群算法在解決優化問題中錶現齣良好的併行性和全跼搜索特性,但由于人為設置參數的影響可能會陷入跼部最優。針對聚類問題的特徵,將魚群算法運用到聚類問題中,在使用自適應步長的魚群算法的基礎上,進一步融閤免疫接種機製,加彊算法對精確解的搜索性能,通過UCI數據集上的實驗分析和比較,錶明算法具有更好的有效性和穩定性。
전통적K-균치취류방법,재취류과정중과도의뢰초시취류중심적선택,동시유우전국수색능력적불족,흔난득도정학적취류중심。어군산법재해결우화문제중표현출량호적병행성화전국수색특성,단유우인위설치삼수적영향가능회함입국부최우。침대취류문제적특정,장어군산법운용도취류문제중,재사용자괄응보장적어군산법적기출상,진일보융합면역접충궤제,가강산법대정학해적수색성능,통과UCI수거집상적실험분석화비교,표명산법구유경호적유효성화은정성。
The traditional K-means algorithm is over-dependent on the choice of the initial cluster centers during the clus-tering process. Meanwhile, due to the lack of global search capability, it is difficult to get the accurate cluster centers. Fish-school algorithm shows good parallelism and global search feature in solving optimization problems, but may fall into local optimal solution because of the artificial parameters. In this paper, it applies fish-school algorithm to the clustering problems according to their characteristics and combines immunity-vaccination mechanism with the fish-school algorithm using adaptive step to strengthen the search performance of the algorithm for the exact solution. The experimental analysis and comparison results on UCI datasets show that the algorithm has better validity and stability.