An Interval Type-2 Fuzzy Neural Network for Cognitive Decisions
Guannan Leng, Anjan Kumar Ray, T.M. McGinnity, Sonya Coleman, Liam Maguire, Philip J. Vance · 2014
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.