计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
20期
110-114
,共5页
K-me doids算法%粒子群算法%相异度矩阵%粗糙集%记忆技术
K-me doids算法%粒子群算法%相異度矩陣%粗糙集%記憶技術
K-me doids산법%입자군산법%상이도구진%조조집%기억기술
K-me doids algorithm%particle swarm optimization%dissimilarity matrix%rough set%memorization
针对K-me doids算法的全局搜索能力弱和迭代计算过程计算量大的不足，提出了一种改进的基于粒子群的粗糙K-medoids算法。该算法通过粒子群算法来改善K-medoids全局搜索能力，通过计算样本集的相异度矩阵来简化粒子群编码，引入粗糙集理论处理边界模糊数据，并利用记忆技术对K-medoids的迭代过程进行优化，降低算法的复杂度。通过对UCI中的Iris、Mushroom数据集测试，该算法的准确率提高，运行时间减少。
針對K-me doids算法的全跼搜索能力弱和迭代計算過程計算量大的不足，提齣瞭一種改進的基于粒子群的粗糙K-medoids算法。該算法通過粒子群算法來改善K-medoids全跼搜索能力，通過計算樣本集的相異度矩陣來簡化粒子群編碼，引入粗糙集理論處理邊界模糊數據，併利用記憶技術對K-medoids的迭代過程進行優化，降低算法的複雜度。通過對UCI中的Iris、Mushroom數據集測試，該算法的準確率提高，運行時間減少。
침대K-me doids산법적전국수색능력약화질대계산과정계산량대적불족，제출료일충개진적기우입자군적조조K-medoids산법。해산법통과입자군산법래개선K-medoids전국수색능력，통과계산양본집적상이도구진래간화입자군편마，인입조조집이론처리변계모호수거，병이용기억기술대K-medoids적질대과정진행우화，강저산법적복잡도。통과대UCI중적Iris、Mushroom수거집측시，해산법적준학솔제고，운행시간감소。
The K-me doids algorithm has the disadvantage of global search ability and large amount of the iterative calcu-lation, this paper proposes an improved rough K-medoids algorithm based on Particle Swarm Optimization(PSO). By introducing PSO to strengthen its global search ability and calculating the dissimilarity matrix of sample set to simplify coding particle swarm, the rough set theory provides a processing method of dealing with the indeterminacy problem of boundary objects. It uses memorization technique to improve K-medoids iterative calculation, to reduce the complexity of the algorithm. Through testing the Iris, Mushroom data set of UCI, the new algorithm’s accuracy is improved and the time is shortened.
