The number of weights per neuron correlates with the rows in matrix 𝑥. Within each layer, the bias is represented as a vector with a size equal to the number of neurons, while the weights are represented as a matrix with dimensions determined by the number of neurons and either the dimension of the input or the number of neurons in the preceding layer. In order to train the ANN, various numerical frameworks such as TensorFlow , PyTorch , and MATLAB may be utilized. For this study, the Neural Network Toolbox of MATLAB was the preferred tool for implementation.