Web shopping expert using new interval type-2 fuzzy reasoning

被引：0
|
作者：
L. Gu
Y. -Q. Zhang
机构：
[1] Georgia State University,Department of Computer Science
来源：
Soft Computing | 2007年 / 11卷
关键词：
Fuzzy logic; Decision support system; Type-2 fuzzy logic sets; Type reduce; System optimizations; Least square method;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Finding a product with high quality and reasonable price online is a difficult task due to uncertainty of Web data and queries. In order to handle the uncertainty problem, the Web Shopping Expert, a new type-2 fuzzy online decision support system, is proposed. In the Web Shopping Expert, a fast interval type-2 fuzzy method is used to directly use all rules with type-1 fuzzy sets to perform type-2 fuzzy reasoning efficiently. The parameters of type-2 fuzzy sets are optimized by a least square method. The Web Shopping Expert based on the interval type-2 fuzzy inference system provides reasonable decisions for online users.
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页码：741 / 751
页数：10
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