摘要
非常规突发事件的风险识别是应急管理亟待解决的难题.综合运用免疫危险理论与计算实验技术,构建了突发事件风险识别的抗体浓度和亲合度的双危险信号模型以及基于相似性交叉与多样性变异的免疫遗传识别算法模型,将非常规突发事件风险识别转化为多峰函数优化问题,运用所提出的算法,发掘非常规突发事件的演化规律,发现最佳应对时机.通过森林火灾算例分析,演示了基于免疫危险理论的非常规突发事件风险识别方法在应急管理中的应用,验证了模型的科学性和可行性.
Risk identifcation for unconventional crisis is one urgent issue of crisis management. Based on the integration of immune danger theory with experimental techniques, double-signal danger model upon antibody concentration and affinity is constructed along with immune genetic identification algorithm upon similarity-crossover and diversity-mutation, which transforms risk identification of unconventional crisis into multi-modal function optimization. The methods can help explore the evolution rules of unconventional crisis and find the optimal response occasion. management is illustrated by empirical analysis The scientificity and feasibility of the methods in crisis of forest fire.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2015年第10期2667-2674,共8页
Systems Engineering-Theory & Practice
基金
国家自然科学基金重大研究计划培育项目(91024020)
国家自然科学基金面上项目(71371148)
安全预警与应急联动技术湖北省协同创新中心开放课题(JD20150105)
武汉市社会科学基金资助课题(14019)
关键词
非常规突发事件
风险识别
免疫危险理论
危险信号函数
免疫遗传算法
unconventional crisis
risk identification
immune danger theory
danger signal function
immune genetic algorithm
