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Estimation of Seismicity Parameters and a Backpropagation Neural Network for Prediction of Earthquake Magnitude in Northeast Region of India

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Case Studies in Building Constructions

Part of the book series: Building Pathology and Rehabilitation ((BUILDING,volume 15))

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Abstract

This study presents the spatial variation of seismicity parameters and artificial neural network (ANN) model for earthquake magnitude prediction in the northeast region of India considering updated earthquake catalogue of magnitude Mw ≥ 4.0 that occurred from year 1731 to 2015 in the study area. The study area has been divided into 17 seismic source zones keeping in view the spatial variation in earthquake occurrences, distribution pattern of events and orientation of seismic sources. Seismicity parameters were estimated for each source zone as well as for the whole study area. The estimated ‘b’ value in this study varies from 0.50 to 0.84 in different seismic source zones and for the whole study area it is found as 0.77. The proposed ANN technique to predict the possible magnitude of earthquakes in the identified seismic source zones is based on feedforward backpropagation neural network model with single hidden layer. Total five input parameters namely, longitude, latitude, elapsed time between two events, cumulative magnitude probability and seismic energy and one output parameter namely, magnitude of earthquakes were used in ANN. The ‘b’ value estimated in this study was used as an input unit in ANN in calculating the cumulative magnitude probability for different zones. The performance of ANN was evaluated by estimating the mean absolute error (MAE), sum of squared error (SSE) and Mean squared error (MSE). And the results obtained in this study show that the ANN model yields good prediction accuracy for earthquake magnitude in NE India.

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Acknowledgements

The authors acknowledge the support of SERB-DST (ECR/2016/001329) to carry out the research studies.

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Authors and Affiliations

  1. Dept of Civil Engineering, NIT Silchar, Silchar, Assam, 788010, India

    Amit Zarola & Arjun Sil

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  1. Amit Zarola
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  2. Arjun Sil
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Correspondence to Arjun Sil .

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  1. CONSTRUCT-LFC, Department of Civil Engineering, Faculty of Engineering, University of Porto, Porto, Portugal

    J.M.P.Q. Delgado

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Zarola, A., Sil, A. (2021). Estimation of Seismicity Parameters and a Backpropagation Neural Network for Prediction of Earthquake Magnitude in Northeast Region of India. In: Delgado, J. (eds) Case Studies in Building Constructions. Building Pathology and Rehabilitation, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-55893-2_3

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  • DOI: https://doi.org/10.1007/978-3-030-55893-2_3

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