The study reported in this paper employed Artificial Neural Networks (ANN) to predict the critical force of the buckling composite structures. The critical force depends upon various factors such as thickness, stacking sequence, etc. These factors have been identified in earlier studies by means of the Finite Elements Method (FEM). The critical force is affected by the above-mentioned factors. Various approaches have been applied in the course of the presented study. Apart from our FEM simulation, the ANN approach has been applied and the results were compared. The main contribution of these two approaches is the estimation of the critical force. The ANN model is trained to predict the critical force for different configurations of input va...
In this paper, an efficient method for performing minimum weight optimization of composite laminates...
WOS: 000281888500008This paper proposes the use of artificial neural networks (ANN) to perfectly pre...
In this paper, we show some different concepts for the use of Artificial Neural Networks in modellin...
The study reported in this paper employed Artificial Neural Networks (ANN) to predict the critical f...
The composite hat-stiffened panel is a typical structure that embodies the concepts of high strength...
Composite hat-stiffened panels are typical composite structures that embody the concept of high stre...
Designing thin-walled structural members is a complex process due to the possibility of multiple ins...
The design process of thin-walled structural members is highly complex due to the possible occurrenc...
Abstract—Environmental awareness today motivates the researchers, worldwide on the studies of natura...
In this paper, an efficient method for performing minimum weight optimization of composite laminates...
In structural stability analyses, determining the critical buckling load is a crucial issue. Regress...
Accurate measurement of the critical buckling stress is crucial in the entire field of structural en...
This paper proposes the use of artificial neural networks (ANN) to predict perfectly the critical bu...
The scope of this study is to examine the development of an artificial neural network (ANN) method f...
The scope of this study is to examine the development of an artificial neural network (ANN) method f...
In this paper, an efficient method for performing minimum weight optimization of composite laminates...
WOS: 000281888500008This paper proposes the use of artificial neural networks (ANN) to perfectly pre...
In this paper, we show some different concepts for the use of Artificial Neural Networks in modellin...
The study reported in this paper employed Artificial Neural Networks (ANN) to predict the critical f...
The composite hat-stiffened panel is a typical structure that embodies the concepts of high strength...
Composite hat-stiffened panels are typical composite structures that embody the concept of high stre...
Designing thin-walled structural members is a complex process due to the possibility of multiple ins...
The design process of thin-walled structural members is highly complex due to the possible occurrenc...
Abstract—Environmental awareness today motivates the researchers, worldwide on the studies of natura...
In this paper, an efficient method for performing minimum weight optimization of composite laminates...
In structural stability analyses, determining the critical buckling load is a crucial issue. Regress...
Accurate measurement of the critical buckling stress is crucial in the entire field of structural en...
This paper proposes the use of artificial neural networks (ANN) to predict perfectly the critical bu...
The scope of this study is to examine the development of an artificial neural network (ANN) method f...
The scope of this study is to examine the development of an artificial neural network (ANN) method f...
In this paper, an efficient method for performing minimum weight optimization of composite laminates...
WOS: 000281888500008This paper proposes the use of artificial neural networks (ANN) to perfectly pre...
In this paper, we show some different concepts for the use of Artificial Neural Networks in modellin...