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Seismic activity prediction using computational intelligence techniques in northern Pakistan

  • Research Article - Solid Earth Sciences
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Abstract

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar’s statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

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Acknowledgements

The authors would like to thank friends and colleagues for nice suggestions, in particular, Mr. Iqbal Murtza for his valuable remarks and guidance. Spanish Ministry of Science and Technology, Junta de Andaluca and University Pablo de Olavide under projects TIN2011-28956-C02, P12-TIC-1728 and APPB813097 are also acknowledged.

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Authors and Affiliations

  1. Centre for Earthquake Studies, National Centre for Physics, Islamabad, Pakistan

    Khawaja M. Asim, Muhammad Awais & Talat Iqbal

  2. Department of Computer Science, Pablo de Olavide University, Seville, Spain

    F. Martínez–Álvarez

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  1. Khawaja M. Asim
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  2. Muhammad Awais
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  3. F. Martínez–Álvarez
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Correspondence to Khawaja M. Asim.

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Asim, K.M., Awais, M., Martínez–Álvarez, F. et al. Seismic activity prediction using computational intelligence techniques in northern Pakistan. Acta Geophys. 65, 919–930 (2017). https://doi.org/10.1007/s11600-017-0082-1

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  • DOI: https://doi.org/10.1007/s11600-017-0082-1

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