【摘要】 针对城市公交运营突发事件危险源复杂、应急信息系统繁多、但未形成某种危险源发生时的应急指挥信息化协同体系的问题,将遗传算法-粗糙集模型应用于公交运营突发事件危险源筛选,区别于传统粗糙集理论,基于多决策属性决策表和与其对应的适应度函数进行危险源筛选。以北京市公交运营为例进行了实例计算和分析,筛选出气象灾害为关键危险源。遗传算法-粗糙集模型在公交运营突发事件危险源筛选问题上表现出良好的可靠性。同时建立了气象灾害危险源情境下的北京市地面公交应急指挥信息化协同体系。更多还原

【Abstract】 The hazard sources of urban bus emergency are complicated and the information systems for emergency respond are diversified. At present, no emergency coordination system is available when emergency occurs suddenly in an urban busing system. Therefore, a genetic algorithm(GA)-rough set theory model was developed to screen the key hazard source in emergence. Different from traditional rough set theory, the hazard source screening problem is based on multi-decision attribute decision data and corresponding fitness function. The bus operation emergency of Beijing was taken as an example, for which meteorological disaster was screened out as the key hazard source. The results show that the GA-rough set model has good reliability on bus emergency hazard source screening. Meanwhile, the emergency coordination system for urban bus emergency under meteorological disaster is established.更多还原