Figure 3.

Illustration of the structure of a multi-layer artificial neural network (ANN). A multilayer ANN consists of 1 or more hidden layers. The network has the ability to correct the feedforward when the input signal enters the network. When the output signal was different from the expected output, the error value was calculated and fed forward to the input to adjust the weight. In the ANN-related parameter settings, the number of hidden layer neurons, the number of hidden layers, and the learning rates affected the accuracy of ANN-based classification.