基于区间推理和AFS结构的模糊分类器  

A Fuzzy Classifier Based on Interval-valued Reasoning and AFS Structure

作　　者：邱望仁[1] 刘陶[1] 刘晓东[2] 

机构地区：[1]景德镇陶瓷学院信息工程学院,江西景德镇333403 [2]大连海事大学数学系,辽宁大连116026

出　　处：《信息与控制》2006年第5期651-656,661,共7页Information and Control

基　　金：国家自然科学基金资助项目(60575039)

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,提出两种分类器的算法,它们分别是建立在区间值推理和AFS结构上的.经Iris数据实验,证明第一种算法分类结果很好,后一算法不仅结果与前面的一样好,而且它还能处理一些描述模糊概念的数据库.这两种算法在分类实践中具有良好的应用前景.*Based on the analysis of interval-valued fuzzy set theory and current fuzzy classifier, two classifier algorithms based on interval-valued reasoning and AFS theory respectively are proposed. Experiments with the Iris data show that the former algorithm has good performance and the latter not only performs better than the former but also can be applied to databases which describe fuzzy concept. These two algorithms have very good prospect in the practice of classification.

关 键 词：区间值模糊集 模糊推理 模糊分类器 模糊匹配函数 AFS结构 

分 类 号：TP37[自动化与计算机技术—计算机系统结构]