Choquet fuzzy integral-based identification

被引：0
|
作者：
Srivastava, S [1 ]
Singh, M [1 ]
Hanmandlu, M [1 ]
机构：
[1] NSIT, New Delhi, India
来源：
2004 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2 | 2004年
关键词：
Choquet fuzzy integral; q-measure; identification;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A Choquet fuzzy Integral based approach to identification of non-linear systems is investigated. The Choquet Integral replaces the maximum (minimum) operator in the information aggregation with a fuzzy integral based neuron. The identification of Choquet integral based fuzzy model is developed with strength of the rules as the input functions and unknown fuzzy densities, subject to q-measure, as the coefficients. This is a significant contribution as it leads to a class of nonadditive fuzzy systems. In addition to it, the use of q-measure provides a more flexible and powerful way of incorporating various fuzzy measures into the Integral. Simulation results show the effectiveness of the identification method.
引用
收藏
页码：1335 / 1340
页数：6
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