Research on intelligent question-answering system for flood emergency decision-making with fusion of GPT and knowledge graph
To enhance the analytical capability of generative pre-trained transformer(GPT)models in emergency manage-ment information processing,aiming to achieve the online assistant decision-making during the emergency response of flood disaster,an intelligent question-answering system of emergency decision-making with the fusion of GPT and knowledge graph(KG-GPT)was proposed.The GPT architecture was improved to identify the key information in the questions,and the knowledge graph was used to reason the knowledge in the emergency field and generate the logical answers.Combining the ac-tual emergency decision-making question and answer data set of flood disaster and compiling the drill script,the system was compared with GPT-2.0 by using the automatic evaluation and expert evaluation methods.The research results show that the system successfully fuses the knowledge graph in the emergency field and GPT model,and can deeply understand the back-ground information of problems and generate the smooth answers.Compared with GPT-2.0,the system offers the decision-makers a faster and more accurate online assistant decision-making tool.The research results can improve the efficiency of emergency information analysis and decision-making in flood disasters.
万方数据
维普
