This paper presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors.

Abstract: This work presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors. In the adopted framework, ...

This work presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors. In the adopted framework, ...

This work presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors by testing two different approaches ...

This paper presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors. A general framework is adopted, ...

This paper presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors. A general framework is adopted, ...

This work presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors. In the adopted framework, ...

The aim of this overview paper is to present the new approaches elaborated at VUJE, Inc. to make the diagnostic systems in the environment of a nuclear power ...

Error backpropagation in feedforward neural network models is a popular learning algorithm that has its roots in nonlinear estimation and optimization.

Evsukoff and Gentil created a recurrent Neuro-Fuzzy system for fault detection and isolation in nuclear reactors. [4]. In their model a fuzzification module is ...