Statistical Prediction of Probabilistic Earthquake Hazard Zonation whit Artificial Neural Networks

Prediction of location of future earthquakes with event probability is useful in reduction of earthquake hazard. Determination of predicted locations has been caused more attention to design, seismic rehabilitation and reliability of structures in these sites. Many theories were proposed in the prediction of occurred time of earthquake. There is not a trusty method for prediction of occurred time of future earthquakes. Many studies have been done in the prediction of magnitude of earthquakes, but there is not any investigation on prediction of earthquake hazard zonation. In this study, the locations that have probability of the event of future earthquake have been predicted by artificial neural networks in Qum and Semnan. Neural networks used in this study can extract to complicate properties of patterns by receipting the interval patterns. Furthermore, the map of earthquake hazard zonation has been drawn. Properties of occurred earthquake were collected since 1903. The most probable event of earthquake in Qum has been predicted 31.6% in center, and 28.9% in north of Semnan.