Analysis of medical rescue strategies based on a rough set and genetic algorithm: A disaster classification perspective. (January 2020)

• Record Type: Journal Article
• Authors: Li, Tanshi; Li, Zhuyi; Zhao, Wei; Li, Xueyan; Zhu, Xin; Pan, Shuxiao; Feng, Cong; Zhao, Yuzhuo; Jia, Lijing; Li, Jing
• Is Part Of: International journal of disaster risk reduction. Volume 42(2020)
• Publication Date: 2020-01
• Subjects: Disaster -- Medical rescue -- Rough set -- Genetic algorithm -- Classification; Emergency management -- Periodicals; Risk management -- Periodicals; Disaster relief -- Periodicals; Hazard mitigation -- Periodicals; 363.34
• DOI: 10.1016/j.ijdrr.2019.101325
• Languages: English
• ISSNs: 2212-4209

Abstract

Abstract: Quantitative research on disaster medical rescue from the perspective of disaster classification can provide a more accurate decision-making foundation for disaster medical rescue management. In this study, the medical features caused by various types of sudden disasters are utilized as the starting point to construct a disaster medical rescue decision table based on the rough set theory. Then, a genetic algorithm is used to analyze the common points of various disaster medical features upon which many disasters are classified. The common features and personality features of disaster medical rescue operations are explored, and systematic recommendations are proposed for medical emergency rescue management based on these features of disaster classification. These results provide theoretical support for the design of disaster relief classification standards, actual plans, and rescue work.