%0 Journal Article
	%A Belkacem Selma and  Boumediene Selma and  Samira Chouraqui and  Hanifi Missoum and  Tourkia Guerzou
	%D 2023
	%J International Journal of Geological and Environmental Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 193, 2023
	%T Artificial Neural Networks Technique for Seismic Hazard Prediction Using Seismic Bumps
	%U https://publications.waset.org/pdf/10012886
	%V 193
	%X Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. Earthquake prediction to prevent the loss of human lives and even property damage is an important factor; that, is why it is crucial to develop techniques for predicting this natural disaster. This study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 104 J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines have been analyzed. The results obtained show that the ANN is able to predict earthquake parameters with  high accuracy; the classification accuracy through neural networks is more than 94%, and the models developed are efficient and robust and depend only weakly on the initial database.
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