A Method of Emergent Event Evolution Reasoning Based on Ontology Cluster and Bayesian Network

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Abstract
Comprehensive real-time event information is critical to policymakers during emergency response and decision-making process. However, the development process of the emergent events has great uncertainty and situational evolutions of emergencies are often difficult to use fixed reasoning mode to attain. For this reason, this paper proposes a new method based on ontology cluster for the evolution reasoning of emergency scenarios, and extends the SWRL rule language to realize scenario deduction, which can apply Bayesian network to perform conditional probability reasoning. A counterpart modeling and modifying of the Bayesian network optimization process is introduced. Besides, the probabilistic interpretation rules of atom components in context evolution are described with detailed query examples of emergency situation deducting and reasoning. The experimental results show that this approach is efficient in describing and capable of calculating the occurrence possibilities of emergent events.
Funding Information
  • National Natural Science Foundation of China (61100133)
  • Science Guidance Project of Education Department of Hubei Province (B20101104)

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