This paper introduces an identifier scheme for identification of non-linear systems with disturbances based on Hybrid Neuro-Fuzzy Network (HNFN) technique. The ...

2016/11/15 · The paper deals with the development of indirect adaptive controllers based on Hybrid Neuro-Fuzzy Network (HNFN) approach for Autonomous ...

Ray T; Anavatti S; Hassanein O, 2013, 'Hybrid Neuro-Fuzzy Network ... Autonomous Underwater Vehicles', Lecture Notes in Computer Science, 7691, pp.

This proposed model has an input-output relationship based upon neural fuzzy network (NFN) model technique to overcome the uncertain external disturbance and ...

... fuzzy neural network', Neurocomputing, 171, pp. 89 - 105, http://dx.doi ... Autonomous Underwater Vehicles', Lecture Notes in Computer Science, 7691, pp.

In this article the use of neural networks in the identification of models for underwater vehicles is discussed. Rather than using a neural network in ...

The paper deals with the development of indirect adaptive controllers based on Hybrid Neuro-Fuzzy Network (HNFN) approach for Autonomous Underwater Vehicles ...

An adaptive neuro-fuzzy identification model for the detection of meat spoilage. ... Neural network adaptive controller for unmanned underwater vehicles. Neural ...

Fuzzy logic and neural network control blocks make up the proposed control design to control the depth and heading angle of autonomous underwater vehicle. The ...

The model is a fuzzy neural network composed of five layers: input (beliefs and desires), fuzzification, commitment, fuzzy intention, and defuzzification layer.