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Prediction of strong events based on the solution of an inverse problem in cellular automaton models Abstract This work states an inverse problem where key parameters are to be recovered in a certain cellular automaton model. Similar to seismicity, the model generates a catalog of events belonging to different energy levels. A method is suggested to reconstruct model parameters from the catalog and to build an algorithm for predicting strong events. For the model imitating a simple linear fault, this approach allows to successfully predict 80\% of strong events with alarm time of about 1% and obtain a slight error in determining the epicenter. The same approach has been modified and tested with simple block models. About 80% of strong events were predicted within the alarm time of about 3% and small errors were obtained in determining epicenters. Back to |