A Novel Fuzzy Rough Granular Neural Network for Classification

DOI

10.2991/ijcis.2011.4.5.27How to use a DOI?

Keywords

Granular computing, fuzzy reflexive relation, fuzzy rough sets, rule based layered network, fuzzy pattern classification.

Abstract

A novel fuzzy rough granular neural network (NFRGNN) based on the multilayer perceptron using backpropagation 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.

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Avatharam Ganivada
AU  - Sankar K. Pal
PY  - 2011
DA  - 2011/09/01
TI  - A Novel Fuzzy Rough Granular Neural Network for Classification
JO  - International Journal of Computational Intelligence Systems
SP  - 1042
EP  - 1051
VL  - 4
IS  - 5
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.5.27
DO  - 10.2991/ijcis.2011.4.5.27
ID  - Ganivada2011
ER  -