计算机工程与应用2017，Vol.53Issue(20)：122-127,6.DOI:10.3778/j.issn.1002-8331.1604-0294
一种输入数据为模糊数的模糊支持向量机
Fuzzy support vector machine based on fuzzy input data
摘要
Abstract
The data that Support Vector Machine(SVM)deals with are mostly precise values,but the SVM cannot be uti-lized 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 func-tion 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.关键词
模糊支持向量机/模糊数/去模糊函数/距离Key words
fuzzy support vector machine/fuzzy number/defuzzification function/distance分类
信息技术与安全科学引用本文复制引用
张新亚,沈菊红,刘楷..一种输入数据为模糊数的模糊支持向量机[J].计算机工程与应用,2017,53(20):122-127,6.基金项目
国家自然科学基金(No.61261043) （No.61261043）
北方民族大学研究生创新项目(校研究生发[2014]6号). （校研究生发[2014]6号）
