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Zoning Iran based on earthquake precursor importance and introducing a main zone using a data-mining process

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  • Pooyan Ramezani Besheli
  • Mehdi Zare
  • Ramezan Ramezani Umali
  • Gholamreza Nakhaeezadeh

Abstract

In the present research, Iran was studied and zoned based on the extent and magnitude of foreshocks before the occurrence of earthquakes larger than magnitude 5 using a data-mining process. The aim of this research is to stress the importance of foreshock precursors for different zones of the country; therefore, these zones will be important for earthquake prediction research based on study of precursors. To conduct this research, foreshock precursors were introduced and then separated from the seismic database for the country considering reliable references during declustering operations. After preparing a foreshock database for the country, clustering operations were performed on it using the self-organizing map (SOM) and k-means methods. Using the silhouette index, it was found that the best classification of foreshocks was to classify them into six main clusters, and then group these clusters using Duncan and Tukey statistical tests for investigation in terms of magnitude. Finally, the terminal sequence of the Zagros–Makran Transition Zone was determined to be the main zone of the country in terms of number, relation, and magnitude of foreshocks before the occurrence of earthquakes of magnitude larger than 5. The Hormozgan region is completely located in this zone; i.e., foreshocks have a very close relation with large earthquakes, and most earthquakes in this region were accompanied by foreshocks of relatively high magnitude. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Pooyan Ramezani Besheli & Mehdi Zare & Ramezan Ramezani Umali & Gholamreza Nakhaeezadeh, 2015. "Zoning Iran based on earthquake precursor importance and introducing a main zone using a data-mining process," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 78(2), pages 821-835, September.
    • Handle: RePEc:spr:nathaz:v:78:y:2015:i:2:p:821-835
    DOI: 10.1007/s11069-015-1745-3
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    References listed on IDEAS

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    1. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, December.
    2. Andrew M. Freed & Jian Lin, 2001. "Delayed triggering of the 1999 Hector Mine earthquake by viscoelastic stress transfer," Nature, Nature, vol. 411(6834), pages 180-183, May.
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    1. Bitkowska Agnieszka & Sliż Piotr & Tenbrink Candace & Piasecka Aleksandra, 2020. "Application of Process Mining on the Example of an Authorized Passenger Car Service Station in Poland," Foundations of Management, Sciendo, vol. 12(1), pages 125-136, January.

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