Predicting the Earthquake Magnitude Using the Multilayer Perceptron Neural Network with Two Hidden Layers
Abstract: Because of the major
disadvantages of previous methods for calculating the magnitude of the
earthquakes, the neural network as a new method is examined. In this paper a
kind of neural network named Multilayer Perceptron (MLP) is used to predict
magnitude of earthquakes. MLP neural network consist of three main layers;
input layer, hidden layer and output layer. Since the best network
configurations such as the best number of hidden nodes and the most appropriate
training method cannot be determined in advance, and also, overtraining is
possible, 128 models of network are evaluated to determine the best prediction
model. By comparing the results of the current method with the real data, it
can be concluded that MLP neural network has high ability in predicting the
magnitude of earthquakes and it’s a very good choice for this purpose.
Keywords: Earthquake
Magnitude; Prediction; Multilayer Perceptron; Neural Network; Two Hidden Layers
Author: Jamal Mahmoudi,
Mohammad Ali Arjomand, Masoud Rezaei, Mohammad Hossein Mohammadi
Journal Code: jptsipilgg160009
