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Author Chandana, S. ♦ Mayorga, R.V.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2006
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Neurons ♦ Computer architecture ♦ Rough sets ♦ Convergence ♦ Neural networks ♦ Intelligent systems ♦ Fuzzy sets ♦ Transfer functions ♦ Uncertainty ♦ Artificial intelligence
Abstract The paper presents a new hybridization methodology involving neural, fuzzy and rough computing. A rough sets based approximation technique has been proposed based on a certain neuro-fuzzy architecture. A new rough neuron composition consisting of a combination of a lower bound neuron and a boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'output excitation factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing rough neural networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.
Description Author affiliation: Univ. of Regina, Regina (Mayorga, R.V.)
ISBN 0780394887
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2006-07-16
Publisher Place Canada
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 338.07 kB
Page Count 7
Starting Page 1966
Ending Page 1972

Source: IEEE Xplore Digital Library