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An Interval Type-2 Fuzzy Neural Network for Cognitive Decisions

Authors:
Gang Leng
Anjan Kumar Ray
Thomas Martin McGinnity
Sonya Coleman
Liam Maguire
Philip Vance

Keywords: interval type-2 fuzzy system; self-organising fuzzy neural network; cognitive decisions; modelling capability; robustness

Abstract:
In an ambient assisted living environment, raw data can often be very noisy making is difficulty to interrupt by a decision and reasoning system. To help reduce the effects of noise, we propose a decision and reasoning system which combines an interval fuzzy system and a self-organising fuzzy neural network (SOFNN) is presented in this paper. The method exploits the use of a trained standard SOFNN structure from a fuzzy neural network to initialise the proposed approach. Simulation results show that the proposed structure is more suitable for uncertain situations demonstrating a high level of robustness.

Pages: 159 to 164

Copyright: Copyright (c) IARIA, 2014

Publication date: May 25, 2014

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-340-7

Location: Venice, Italy

Dates: from May 25, 2014 to May 29, 2014