Fuzzy nonlinear regressions based on fuzzy choquet integrals

被引：0
|
作者：
Ji, Ai-bing [1 ]
Qiu, Hong-jie [1 ]
Pang, Jiahong [1 ]
机构：
[1] Hebei Univ, Coll Publ Hlth, Baoding 071000, Hebei, Peoples R China
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2015年 / 28卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Non-additive measures; fuzzy-valued fuzzy measure; fuzzy choquet integral; nonlinear fuzzy multiregression; NEURAL-NETWORKS; ALGORITHM; MODEL;
D O I：
10.3233/IFS-141371
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we first introduce two kinds of aggregation tools: fuzzy Choquet integrals, one is the fuzzy Choquet integral of fuzzy-valued functions with respect to fuzzy measure, the another is the fuzzy Choquet integral of real-valued functions with respect to fuzzy-valued fuzzy measure. Then using the nonadditive crisp/fuzzy set function to describe the interaction among attributes, two kinds of new fuzzy nonlinear multiregression are established based on fuzzy Choquet integrals, it can catch the interaction among the predictive attributes toward the objective attribute, Such models are generalizations of the traditional fuzzy linear multiregression.
引用
收藏
页码：897 / 903
页数：7
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