Journal
SOFT COMPUTING
Volume 21, Issue 19, Pages 5805-5813Publisher
SPRINGER
DOI: 10.1007/s00500-016-2158-2
Keywords
Earthquake prediction; Bat Algorithm; Artificial neural network; Optimization technique
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Earthquakes are natural disasters which may result in heavy losses. Accurate prediction of the time and intensity of future earthquakes can lead to minimizing losses due to earthquakes. Anumber of earthquake predictions have been proposed based on mathematical and statistical models. In this paper, we present an earthquake prediction technique using Bat Algorithm (BA) and Feed Forward Neural Network (FFNN). The BA is used to train the weights of the FFNN to predict future earthquakes on the basis of past input data. Experimental results show that our proposed approach is highly comparable and more stable than Back Propagation Neural Network (BPNN) with respect to accuracy.
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