Tsunami Vulnerability Analysis of Makran Subduction Zone through Fuzzy Logic

Abstract

Tsunamis are among the most terrifying natural hazards, causing significant loss of life and property and impacting our society’s human, economic, and social aspects. Given their destructive nature, developing effective techniques for tsunami observation and demolition reduction is crucial. This study proposes a novel tsunami detection and alert system utilizing fuzzy logic to mitigate these impacts. The primary objective of this research is to develop and implement a fuzzy logic-based tsunami prediction system that generates alerts indicating the likelihood of a tsunami-categorized as definite, certain, average, or rare. In the present study, we employ the fuzzy logic technique in MATLAB, using various defuzzification techniques available in the MATLAB fuzzy logic toolbox. The calculated values for the tsunami alert system in the Makran Subduction Zone are as follows: rare (1.91), average (4.75), certain (6.75), and definite (8.8). The designed tsunami alert system and model can predict tsunamis automatically and manually, potentially saving many lives more effectively than previous methods. The research objectives of this study are to (1) develop a fuzzy logic-based model for tsunami prediction, (2) implement the model using MATLAB, and (3) evaluate the model’s performance in generating accurate tsunami alerts.