A Novel Fuzzy Rough Granular Neural Network for Classification

被引：0
|
作者：
Ganivada A. [1 ]
Pal S.K. [1 ]
机构：
[1] Center for Soft Computing Research, Indian Statistical Institute, Kolkata
来源：
International Journal of Computational Intelligence Systems | 2011年 / 4卷 / 5期
关键词：
fuzzy pattern classification; fuzzy reflexive relation; fuzzy rough sets; Granular computing; rule based layered network;
D O I：
10.2991/ijcis.2011.4.5.27
中图分类号：
学科分类号：
摘要：
A novel fuzzy rough granular neural network (NFRGNN) based on the multilayer perceptron using back-propagation algorithm is described for fuzzy classification of patterns. We provide a development strategy of knowledge extraction from data using fuzzy rough set theoretic techniques. Extracted knowledge is then encoded into the network in the form of initial weights. The granular input vector is presented to the network while the target vector is provided in terms of membership values and zeros. The superiority of NFRGNN is demonstrated on several real life data sets. © 2011, the authors.
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页码：1042 / 1051
页数：9
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