Seismic data analysis using feed forward BP neural network model for earthquake prediction

Earthquakes are one of the most devastating and costly natural risks that a country faces, as they occur without notice and can result in major injuries or the loss of human lives as a result of damage to the destruction of a large number of houses, buildings, and other rigid structures. The point of this review is to assess the exhibition of Artificial Intelligence strategy in foreseeing the following event tremor utilizing the seismic wave signals. We present a three-layer feed forward BP neural organization model to find factors related to quake greatness M and seven other numerically determined boundaries. As info and target vectors, seismicity markers are utilized.