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融入监督信息的k—mean聚类瓜蓟马预警模型
引用本文:陈志民,李亭,杨敬锋,彭晓琴.融入监督信息的k—mean聚类瓜蓟马预警模型[J].安徽农业科学,2009,37(30):14738-14739.
作者姓名:陈志民  李亭  杨敬锋  彭晓琴
作者单位:陈志民(华南农业大学公共基础课实验教学中心,广东,广州,510642);李亭(中山火炬职业技术学院,广东,中山,528436);杨敬锋(华南农业大学公共基础课实验教学中心,广东,广州,510642;广东瑞图万方科技有限公司,广东,顺德,528305);彭晓琴(西南财经大学天府学院,四川,绵阳,651000) 
基金项目:华南农业大学校长基金项目 
摘    要:目的]为提高瓜蓟马病虫害的预警效果。方法]采用k-mean聚类建立了瓜蓟马预警模型,并针对瓜蓟马数据中在k-mean聚类算法下难以判断的情况,引入了监督信息,即模糊关联规则进行进一步划分。结果]引入监督信息的k-mean聚类算法的预警准确率比最近邻算法、k-mean聚类和支持向量机预警准确率都要高。结论]k-mean聚类过程中引入模糊关联规则能较有效地提高预警准确率。

关 键 词:预警  k-mean聚类  模糊关联规则  瓜蓟马

The Warning Model of Melon Thrips Based on k-mean Clustering Combining Fuzzy Association Rules Algorithm
CHEN Zhi-min et al.The Warning Model of Melon Thrips Based on k-mean Clustering Combining Fuzzy Association Rules Algorithm[J].Journal of Anhui Agricultural Sciences,2009,37(30):14738-14739.
Authors:CHEN Zhi-min
Institution:CHEN Zhi-min et al (Center of Experimental Teaching for Common Basic Courses,South China Agricultural University,Guangzhou,Guangdong 510642)
Abstract:Objective] The aim of the study was to improve warning effect of melon thrips diseases and insect pests.Method]The warning model of melon thrips by k-mean Clustering was firstly established.Considering the challenge of quantity of samples that were difficult to classify in the process of k-mean Clustering,an iterative algorithm combining fuzzy association rules was discussed.Result] The study showed that the warning accuracy of k-mean Clustering combining fuzzy association rules provided a higher accurac...
Keywords:Warning  k-mean Clustering  Fuzzy association rules  Melon thrips  
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