ABSTRACT: Fatigue behavior of unidirectional glass fiber/epoxy composites under tension–tension and tension–compression loading is important in the design of composite structures. Adaptive neuro-fuzzy modeling was successfully used to model the relationship between the input/output variables of fatigue behavior of unidirectional glass fiber/epoxy composites. The experimental input variables were the maximum stress, fiber orientation, and stress ratio, while the output variable was the number of cycles to failure. In comparison with previous results obtained using neural networks only, the proposed hybrid neuro-fuzzy method gave more accurate fatigue life predictions. KEY WORDS: composites, fatigue life, neuro-fuzzy
In this study, the informative bounds of neural networks (NN) prediction with respect to the utiliza...
Because of the relatively large number of possible failure mechanisms in fibre reinforced composite ...
Modeling of fatigue life of composite materials under various loading and environment conditions bec...
Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference syste...
Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference syste...
The aim of this work is to study the effect of fiber prestress on the impact strength and fracture t...
The aim of this work is to study the effect of fiber prestress on the impact strength and fracture t...
The aim of this work is to study the effect of fiber prestress on the impact strength and fracture t...
An artificial neural network has been proved to be a sufficient tool for modelling fatigue life of m...
In the current study, Multi Layer Perceptron (MLP) based neural networks (NN) model with one hidden ...
Fatigue behavior of glass fiber reinforced epoxy composite materials has been studied analytically. ...
In the present study an Artificial Neural Network (ANN) model is developed for fatigue life predicti...
A detailed review on fatigue damage of unidirectional fiber composites and life prediction is covere...
A detailed review on fatiguedamage of unidirectional fiber compositesand life prediction is coveredi...
A detailed review on fatiguedamage of unidirectional fiber compositesand life prediction is coveredi...
In this study, the informative bounds of neural networks (NN) prediction with respect to the utiliza...
Because of the relatively large number of possible failure mechanisms in fibre reinforced composite ...
Modeling of fatigue life of composite materials under various loading and environment conditions bec...
Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference syste...
Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference syste...
The aim of this work is to study the effect of fiber prestress on the impact strength and fracture t...
The aim of this work is to study the effect of fiber prestress on the impact strength and fracture t...
The aim of this work is to study the effect of fiber prestress on the impact strength and fracture t...
An artificial neural network has been proved to be a sufficient tool for modelling fatigue life of m...
In the current study, Multi Layer Perceptron (MLP) based neural networks (NN) model with one hidden ...
Fatigue behavior of glass fiber reinforced epoxy composite materials has been studied analytically. ...
In the present study an Artificial Neural Network (ANN) model is developed for fatigue life predicti...
A detailed review on fatigue damage of unidirectional fiber composites and life prediction is covere...
A detailed review on fatiguedamage of unidirectional fiber compositesand life prediction is coveredi...
A detailed review on fatiguedamage of unidirectional fiber compositesand life prediction is coveredi...
In this study, the informative bounds of neural networks (NN) prediction with respect to the utiliza...
Because of the relatively large number of possible failure mechanisms in fibre reinforced composite ...
Modeling of fatigue life of composite materials under various loading and environment conditions bec...