Research On Emergency Response Mechanism Of Fire Incident Based On Knowledge Reasoning

The sudden outbreak of the new crown pneumonia(COVID-19)at the end of 2019 has caused immeasurable losses to my country’s economic and social development,and at the same time posed a major challenge to the emergency management of public emergencies.The establishment of an efficient,orderly,scientifically standardized,and multi-departmental coordinated response mechanism for public emergencies and an intelligent emergency decisionmaking plan is of great significance to the stable development of society.Aiming at the problems of low level of refinement,single decision-making services,and insufficient intelligence in the existing emergency response decision support models,this study takes emergency fire incidents in public emergencies as the research object,based on knowledge graph technology and combined with case-based reasoning and rule-based reasoning method,research the intelligent decision-making reasoning mechanism in the emergency decision-making process,and form the generation method of intelligent emergency response decision plan;finally develop the knowledge reasoning engine of emergency response decision-making,so as to realize the transformation of data into knowledge and decision-making,and make emergency decision-making.It provides real-time,accurate and standardized intelligent decision support when making decisions.The main research work of this thesis includes the followings:(1)to construct a knowledge graph of emergencies.Aiming at the frequent occurrence of fire incidents,the uneven distribution of emergency resources,and the lack of direct correlation structure,a method for constructing a knowledge graph of emergency fire incidents is proposed.Use knowledge extraction technology to extract emergency fire event information from related websites as instance information representing the event,use Protégé to construct the conceptual hierarchical relationship of the knowledge graph,and add instance information on the basis of the existing data model to form a fire knowledge graph;Introduce structured knowledge such as external medical information,police information and fire information,and map them into medical resource knowledge graph,police resource knowledge graph,and fire resource knowledge graph respectively,and merge the above multiple knowledge graphs in an entity-aligned manner.Create a knowledge graph of emergencies,realize the sharing and reuse of emergency response knowledge,and support the visualization of emergencies information and the reasoning of emergency response plans.(2)to design knowledge reasoning model.Combining Case-Based Reasoning(CBR)and Rule-Based Reasoning(RBR)knowledge reasoning models,first find similar historical emergencies through case matching,and on this basis,according to expert advice and Actual emergency rescue needs construct SWRL(Semantic Web Rule Language)rules,and design a knowledge reasoning engine to reason out a suitable emergency decision plan.(3)to optimize emergency response plan.According to the emergency decision plan generated by knowledge reasoning,the ant colony optimization algorithm is used to optimize the multiple plans inferred,and the optimal emergency plan is pushed out on the decision-making platform for decision makers to choose and implement.In this research,a knowledge graph of emergency fire incidents was constructed,and a prototype system of emergency decision-making platform based on case-based reasoning and SWRL rule-based reasoning was designed and implemented.Finally,the proposed method is verified by an example.