基于粗糙集的应急案例中概率规则挖掘方法

应急案例作为描述突发事件发生、发展及应对过程的文本,蕴含了潜在的规律与宝贵的经验。为了挖掘应急案例中各要素间潜在的关联关系,构建出基于粗糙集的应急案例中概率规则挖掘方法。首先,构建出应急案例知识五元组,描述应急案例共性特征,并将诸多应急案例信息组织成一张应急案例决策表;然后,应用遗传算法对应急案例决策表进行属性约简,进而获取概率规则;最后,以大兴安岭林区50起重特大火灾案例为例,阐述方法的具体执行过程,并通过两组测试实验证明了方法的可行性和有效性。该方法描述了应急案例的共性本体特征,具有较高的可重用性,有利于为决策者采取应急管理措施提供决策支持。

Probability Rule Mining in Emergency Cases Based on Rough Set

As texts describing the process of occurrence, development and response of emergencies, emergency cases contain underlying laws and valuable experience. In order to mine the potential relationship among the elements in the emergency cases, the probability rule mining method based on rough set is developed. First, we build a knowledge quintuple to describe the common features of emergency cases, and the information of emergency cases are organized into a decision table; then we use genetic algorithms to reduce the attributes of the decision table of emergency cases, and thus the probability rules can be acquired. Finally, taking the case of 50 cases of heavy fire in Daxinganling forest area as an example, the concrete implementation process of the method is expounded, and two groups of testing experiments prove the feasibility and validity of the method. This method describes the common ontology characteristics of emergency cases, having high reusability, and it is helpful to provide decision support for decision-makers to take emergency management measures.