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Neuroevolution-Based Earthquake Intensity Classification for Onsite Earthquake Early Warning

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Machine Learning, Image Processing, Network Security and Data Sciences

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 946))

Abstract

Earthquake warning systems are adopted as the last resort for providing automated actions preventing secondary hazards due to earthquakes. However, existing methodologies do not provide site-specific warnings related to the intensity of the earthquake at the warning site. Moreover, the use of evolutionary techniques is also not explored for earthquake early warning (EEW). In this article, a warning methodology for onsite alert during a strong earthquake (Modified Mercalli Intensity > V) with potential for damage is proposed. Neuroevolutionary technique is applied on a balanced dataset to enhance precision and recall from 64.09% and 46.68% to 95.03% and 94.47%, respectively, after the proposed dataset balancing, which provided 90.02% warning accuracy.

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Authors and Affiliations

  1. Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India

    Siddhartha Sarkar, Anubrata Roy, Bhargab Das & Satish Kumar

  2. CSIR-Central Scientific Instruments Organization (CSIR-CSIO), Chandigarh, 160030, India

    Siddhartha Sarkar, Bhargab Das & Satish Kumar

Authors
  1. Siddhartha Sarkar
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  2. Anubrata Roy
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  3. Bhargab Das
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  4. Satish Kumar
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Corresponding author

Correspondence to Siddhartha Sarkar .

Editor information

Editors and Affiliations

  1. Department of Information Technology, National Institute of Technology Raipur, Raipur, Chhattisgarh, India

    Rajesh Doriya

  2. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, India

    Badal Soni

  3. Indian Institute of Information Technology, Pune, India

    Anupam Shukla

  4. Faculty of Science and Forestry, School of Computing, University of Eastern Finland, Kuopio, Finland

    **ao-Zhi Gao

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Sarkar, S., Roy, A., Das, B., Kumar, S. (2023). Neuroevolution-Based Earthquake Intensity Classification for Onsite Earthquake Early Warning. In: Doriya, R., Soni, B., Shukla, A., Gao, XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. Lecture Notes in Electrical Engineering, vol 946. Springer, Singapore. https://doi.org/10.1007/978-981-19-5868-7_26

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  • DOI: https://doi.org/10.1007/978-981-19-5868-7_26

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