..., the parameters of excavation design were going to be optimized by adopting the approximate excavation performance using the response surface generated by artificial neural network (ANN) model. Firstly, the training data was generated using numerical studies. Multi-staged 2D plain strain models were adopted...

... of artificial neural networks is not an easy task and requires sophisticated modeling techniques, experience, deep knowledge of engineering and a vast amount of experimental data. Upstream Oil & Gas failure mode ANN model machine learning strength artificial neural network determination Rock...

... problem, which belongs to the model Idenllflcalion in inverse problem theory. Since the artificial neural network (ANN) has powerful nonlinear mapping and self-learning abilities, it provides a new approach for solving this inverse problem, The authors have set up six nonlinear ANN models of Constitutive...