Title: Application of multi-criteria decision-making approach using TOPSIS to identify the vulnerable time zone of earthquake time series signal

Authors: Prasenjit Das; Debabrata Datta; S. Suman Rajest; L. Maria Michael Visuwasam; Anuradha Thakare; J. Cypto

Addresses: Department of Computer Science and Engineering, MCKV Institute of Engineering, Howrah, West Bengal, India ' Department of Information Technology, Heritage Institute of Technology Kolkata, West Bengal, India ' Department of Research and Development (R&D) and International Student Affairs (ISA), Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India ' Department of Artificial Intelligence and Data Science, R.M.K. College of Engineering and Technology, Puduvoyal, Chennai, Tamil Nadu, India ' Department of Computer Engineering, Pimpri Chinchwad College of Engineering, Pune, India ' Department of Computer Science Engineering, SRM Institute of Science and Technology, Ramapuram Campus, Chennai, Tamil Nadu, India

Abstract: Conventional analysis of time series signals representing earthquakes does not provide any clue about the vulnerability of such disastrous events. Time series signals contain P and S waves, which can detect earthquake epicentres. Due to the failure of the old method for determining earthquake susceptibility over time, decision-making is needed. This research suggests a multi-criteria decision-making method to determine earthquake signal risk time zones. This study used TOPSIS for this job. TOPSIS ranks greatest and worst resemblance to positive and negative ideal solutions. Alternatives and criteria constitute the decision matrix. Segmenting the earthquake's duration creates alternate time zones, and seismic signal dynamics are used to set criteria. Statistical mean and standard deviation are two criteria among many. Other criteria include Hurst exponent, power spectrum maximum amplitude, and segmented signal anomaly (assumed as alternate). The proposed approach was tested using Indian Meteorological Department Bhuj earthquake data. The paper describes how to evaluate criteria for a time zone alternative. To simplify computation, earthquake incidence is separated into 14 equal-length time segments. Results demonstrate that the proposed method accurately detects earthquake time series signal sensitive time zones.

Keywords: earthquake time series; hurst exponent; multi-criteria decision-making approach; technique for order of preference by similarity to ideal solution; TOPSIS; vulnerable time zone; earthquake time series signal; sum of additive weighting; SAW; analytical hierarchical process; AHP.

DOI: 10.1504/IJCCBS.2024.139099

International Journal of Critical Computer-Based Systems, 2024 Vol.11 No.1/2, pp.30 - 47

Received: 31 May 2023
Accepted: 20 Dec 2023
Published online: 13 Jun 2024 *

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