关键词: 模糊支持向量机, 模糊数, 去模糊函数, 距离

Abstract: The data that Support Vector Machine （SVM） deals with are mostly precise values, but the SVM cannot be utilized when training samples involving in fuzzy information. Based on this, in response to the classification problem that input data are fuzzy numbers, a novel Fuzzy SVM （FSVM*） with defuzzification function is proposed. This algorithm constructs defuzzification function by taking the distance between fuzzy numbers as the metric for defuzzification of fuzzy numbers to convert fuzzy numbers into precise values, and classifies the fuzzy data by using defuzzification function and fuzzy SVM in combination at the same time. The experimental results show that the  model in this paper is more effective compared to the FSVDD* proposed by Forghani.

Key words: fuzzy support vector machine, fuzzy number, defuzzification function, distance