Chaotic seismic signal modeling based on noise and earthquake anomaly detection

Since ancient times, people have tried to predict earthquakes using simple perceptions such as animal behavior. The prediction of the time and strength an earthquake is primary concern. In this study chaotic signal modeling used based on noise detecting anomalies before artificial neural networks (ANNs). Artificial are efficient tools for solving complex problems identification. study, effective features model obtained considering detection five minutes occurrence. Neuro-fuzzy classifier MLP network approaches showed acceptable accuracy 84.6491% 82.8947%, respectively. Results demonstrate that proposed method seismic anomaly earthquake.