Seismic Microzonation and Future Forecasting of Earthquakes in Western Anatolia through K-Means Clustering Analysis with Magnitude Volatility Detection by Entropy Approaches

Author:

Karakavak Hatice Nur1,Cekim Hatice Oncel1,Kadilar Gamze Ozel1,Tekin Senem2

Affiliation:

1. Hacettepe University: Hacettepe Universitesi

2. Adiyaman University: Adiyaman Universitesi

Abstract

Abstract

Western Anatolia stands out as one of the globally active seismic regions. The paleoseismic history of numerous significant faults in this area, including information about recurrence intervals of damaging earthquakes, magnitude, displacement, and slip rates, remains inadequately understood. The extensive crustal extension at the regional level has given rise to significant horst-graben systems delineated by kilometer-scale normal faults, particularly in carbonate formations, where vertical crustal displacements have taken place. We categorize earthquakes with a k-means clustering algorithm in Western Anatolia from 1900 to 2021 based on specific characteristics or patterns present in the data. Additionally, we explore the volatility in depth and size within each cluster using approximate and sample entropy methods. These entropy measures offer valuable insights into the complexity and irregularity of earthquake patterns in different zones. The findings indicate that to understand seismic activity in the Aegean region comprehensively, it needs to be analyzed by dividing it into three regions using the k-means clustering algorithm. Entropy procedures are implemented to validate that the identified regions accurately depict the seismic patterns. The long-short-term memory (LSTM) method obtains separate earthquake magnitude predictions for each of the three regions. When these values are evaluated with the root mean squared error (RMSE) criterion for the three regions with the actual values, the train data gives strong results with 0.30 and the test data with 0.49 on average. The outcomes demonstrate that the future forecast for each region exhibits unique trends, predicting larger earthquakes in the second segment.

Publisher

Research Square Platform LLC

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