Analysis of medical rescue strategies based on a rough set and genetic algorithm: A disaster classification perspective

被引：7
|
作者：
Li, Tanshi [1 ]
Li, Zhuyi [2 ]
Zhao, Wei [1 ,3 ]
Li, Xueyan [4 ]
Zhu, Xin [4 ]
Pan, Shuxiao [3 ]
Feng, Cong [1 ]
Zhao, Yuzhuo [1 ]
Jia, Lijing [1 ]
Li, Jing [3 ]
机构：
[1] Chinese Peoples Liberat Army Gen Hosp, Beijing, Peoples R China
[2] Natl Univ Singapore, Ind Syst Engn & Management, Singapore, Singapore
[3] Beijing Jiaotong Univ, Sch Econ & Management, Beijing, Peoples R China
[4] Beijing Union Univ, Management Sch, Beijing, Peoples R China
来源：
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION | 2020年 / 42卷
基金：
中国国家自然科学基金;
关键词：
Disaster; Medical rescue; Rough set; Genetic algorithm; Classification; MODEL; DIAGNOSIS;
D O I：
10.1016/j.ijdrr.2019.101325
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
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.
引用
收藏
页数：15
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