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Earth Science Informatics

, Volume 12, Issue 4, pp 513–524 | Cite as

Prediction of earthquake magnitude using adaptive neuro fuzzy inference system

  • Amiya PanditEmail author
  • Kishore Chandra Biswal
Research Article
  • 51 Downloads

Abstract

The present work emphasizes forecasting the occurrence of earth- quakes using a smart and intelligent tool called adaptive neuro-fuzzy inference system(ANFIS). ANFIS can be considered as the fusion of artificial neural networking and fuzzy inference system, which is the smarter version of predicting tool. For this purpose information regarding forty-five real earthquakes are collected from different regions. During the period of 1933 and 1985, earth- quakes from different stations are assembled having magnitude not less than 5. Thereupon, two algorithms are used to develop a model with ANFIS, which tries to produce a better prediction of earthquake magnitude. The higher mag- nitude of earthquakes leads to devastating the life and economy, hence for the safety of the vicinity, the prediction of earthquake magnitude can be a life- saving approach which is quite challenging. Adopting this approach is a very fast and economic way of prediction. Out of grid partitioning and subtractive clustering, subtractive clustering is found to be matchless in a prediction of earthquake magnitude for the data selected in this research.

Keywords

Prediction Earthquake occurrence ANFIS 

Notes

Acknowledgements

Thank you to the unanimous reviewer for providing the valuable comments.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Civil EngineeringNational Institute of TechnologyRourkelaIndia

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