The scope of this study is to examine the development of an artificial neural network (ANN) method for the prediction of maximum failure loads of two serial pinned/bolted E-glass reinforced epoxy composite joints. The experimental data provided from the previous study with different geometrical parameters without preload moments and various applied preload moments were used for developing the ANN model. Comparisons of ANN results with desired values pointed out that there is an excellent agreement between input and output variables of the experimental data. Consequently, ANN was showed to be a suitable powerful tool for the prediction of maximum failure loads of two serial pinned/bolted composite joints
In this work, the ultimate strength of aluminum/silicon carbide (Al/SiC) composites was predicted by...
The study reported in this paper employed Artificial Neural Networks (ANN) to predict the critical f...
In this study, a static shear force and fatigue life prediction model was developed using artificial...
The scope of this study is to examine the development of an artificial neural network (ANN) method f...
The aim of this study is to investigate the improvement of an artificial neural network (ANN) method...
WOS: 000278072500006The aim of this study is to investigate the improvement of an artificial neural ...
Abstract—Environmental awareness today motivates the researchers, worldwide on the studies of natura...
The objective of this paper was to predict the failure load in single lap adhesive joints subjected ...
AbstractThe objective of this paper was to predict the failure load in single lap adhesive joints su...
The present study deals with the use of artificial neural networks ANN in predicting the ultimate lo...
Abstract- The objective of this paper was to predict the failure load of carbon/epoxy composite test...
Composite hat-stiffened panels are typical composite structures that embody the concept of high stre...
Artificial neural networks (ANNs) were used to predict the residual strength of glass fibre-reinforc...
A three layer feed forward artificial neural network (ANN) model having three input neurons, one out...
Mechanical joining and adhesive bonding provide convenience for manufacturing of complex structures,...
In this work, the ultimate strength of aluminum/silicon carbide (Al/SiC) composites was predicted by...
The study reported in this paper employed Artificial Neural Networks (ANN) to predict the critical f...
In this study, a static shear force and fatigue life prediction model was developed using artificial...
The scope of this study is to examine the development of an artificial neural network (ANN) method f...
The aim of this study is to investigate the improvement of an artificial neural network (ANN) method...
WOS: 000278072500006The aim of this study is to investigate the improvement of an artificial neural ...
Abstract—Environmental awareness today motivates the researchers, worldwide on the studies of natura...
The objective of this paper was to predict the failure load in single lap adhesive joints subjected ...
AbstractThe objective of this paper was to predict the failure load in single lap adhesive joints su...
The present study deals with the use of artificial neural networks ANN in predicting the ultimate lo...
Abstract- The objective of this paper was to predict the failure load of carbon/epoxy composite test...
Composite hat-stiffened panels are typical composite structures that embody the concept of high stre...
Artificial neural networks (ANNs) were used to predict the residual strength of glass fibre-reinforc...
A three layer feed forward artificial neural network (ANN) model having three input neurons, one out...
Mechanical joining and adhesive bonding provide convenience for manufacturing of complex structures,...
In this work, the ultimate strength of aluminum/silicon carbide (Al/SiC) composites was predicted by...
The study reported in this paper employed Artificial Neural Networks (ANN) to predict the critical f...
In this study, a static shear force and fatigue life prediction model was developed using artificial...