Rough Set Approach for Group Evacuation Behavior Analysis in Passenger Transport Hub Area

Abstract

Evacuation behavior analysis is deemed to be one aspect of evacuation planning. However, existing studies have not discussed group evacuation decision-making in the face of disagreement among decision makers. In this paper, rough set theory is applied to analyze group evacuation decision-making in passenger transport hub area with various groups including kin, lover, friend, colleague, and classmate. In the approach, improved tabu search-based attribute reduction is proposed to find the minimal subset of attributes required to fully describe the information of group evacuation decision-making, and value reduction algorithm based on knowledge granulation is used to generate rules of group evacuation decision-making. Cross-validation procedure is adopted to estimate the performance of rough set theory. Experimental results indicate that rough set theory has favorable performance. Thus, the proposed approach provides a new way for evacuation behavior analysis.