基于区间推理的模糊分类器  

Fuzzy classifier based on interval-valued reasoning

作　　者：邱望仁[1] 刘陶[2] 丁蕊[1] 刘晓东[1] 

机构地区：[1]大连海事大学数学系,辽宁大连116026 [2]景德镇陶瓷学院计算机系,江西景德镇333001

出　　处：《大连海事大学学报》2005年第4期103-106,110,共5页Journal of Dalian Maritime University

基　　金：国家自然科学基金资助项目(60174014)

摘　　要：在分析区间值模糊集理论和现有模糊分类器的基础上,提出一种新的基于区间值推理的模糊分类器的设计方法,并且对R.A.Fisher的iris数据库进行了分类实验处理,结果证明其分类的正确率超过90%,而且该方法计算简便,运行速度快,因而该分类器的设计方法具有良好的实际应用前景.Based on the analysis of interval-valued fuzzy set theory and the existing fuzzy classifiers, a new algorithm created with the interval-valued reasoning theory was proposed and applied to the Iris data created by R.A. Fisher. The result shows that more than 90 percent of the data are classified rightly and the computation is simple and quick. So this algorithm maybe helpful for the real-world.

关 键 词：模糊数学 区间值模糊集 模糊匹配函数 模糊识别 分类器 

分 类 号：O159[理学—数学]