Selection of appropriate defuzzification methods using application specific properties 论文
1997IEEE Transactions on Fuzzy Systems引用 225
Fuzzy Logic and Control SystemsNeural Networks and ApplicationsMulti-Criteria Decision Making
摘要
Defuzzification is used to transform fuzzy inference results into crisp output. The standard defuzzification methods fail in some applications. It is, therefore, important to select appropriate defuzzification methods depending on the application. This paper presents some of the most important defuzzification methods and investigates their properties. With three application examples, it illustrates how to select appropriate defuzzification methods using application specific properties.