Application of MCDM Model Rough DIBR - Fuzzy LBWA - BONFERRONI and Decision Support System DEXi for the Improvement of Earthquake Risk Level Assessment

Abstract

Abstract Effective decision-making across various domains of society necessitates the adept use of appropriate methods and software to achieve optimal outcomes. This need becomes especially critical in situations where human lives are in jeopardy, and substantial material damages are at stake. The escalating prevalence of natural disasters worldwide highlights the intrinsic threat they pose to protected values, underscoring the importance of comprehensive risk assessments. The paper explore the implementation of the software DEXi in conjunction with DIBR (Defining Interrelationships Between Ranked criteria) method in a rough environment and Fuzzy LBWA (Level Based Weight Assessment) method. The utilization of the Bonferroni aggregator further enhances the earthquake risk level assessment for protected values in the Republic of Serbia. The Rough DIBR and Fuzzy LBWA methods play a pivotal role in determining the criteria weights, and their values are aggregated with the Bonferroni aggregator. The risk assessment process is conducted using the Decision Support System (DSS) called DEXi. Proposed model undergoes rigorous testing, with authentic data sourced from official Disaster Risk Assessments of three cities and five municipalities in the Republic of Serbia. The validation process firmly establishes the model's credibility, laying a robust foundation for improved earthquake risk assessment practices.