基于精简模糊分类关联规则分组模糊判决方法.pdfVIP

2008 3 3 : 2008) a a b c a 杨敬锋, 薛月菊 , 胡月明, 陈志民, 陈 强 ( a. , b. , c. , 510642) : , . , , , , , . , 32 , 922835% , 0005 32 50039 % . : ; ; ; ; : TP 18 : A Grouping uzzy decision based on simpli ied uzzy classi ication association rules YANG Jing eng, XUE Yueju, HU Yueming, CHEN Zhimin, CHEN Qiang ( South China Agricultural University , Guangzhou 510642 , China) Abstract: To improve the intelligibility and e iciency o knowledge expression or the land evaluation , a land evaluation method combining simpli ied uzzy classi ication association rules with uzzy decision is proposed in this paper. To reduce the complexity o the land evaluation models and improve the e iciency and intellig ibility o uzzy classi ication association rules urther, an algorithm to eliminate redundant rules or obtaining the simpli ied uzzy classi ication association rules is presented. In addition , considering the challenge o a ew samples that are di icult to classi y the process o uzzy decision , an iterative algorithm or grouping uzzy decision or datasets is discussed. The results o experiments demonstrate that by u sing only 32 simpli ied uzzy classi ication association rules, accuracy o area o land evaluation can reach 922835 percent . It provides a higher precision w ith the accuracy improved by 50039% , comparing w ith the results o the method combining 32 original uzzy classi ication association rules with uzzy decision w hen minimum support is 0005 . Key wo