首页|基于大模型决策的故障树智能问答方法研究

基于大模型决策的故障树智能问答方法研究

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故障树问答是基于故障树的一种智能问答形式,效率和准确性的提升是关键课题,为此提出了一种基于大模型决策的新方法.将故障树转化为有向无环图,并通过整合深度学习和自然语言处理技术,利用大模型决策技术构建智能问答系统,该系统能够有效地理解并回答与故障树相关的各类问题,解决了多个关键技术难题.针对不同类型和规模的故障树模型,通过实验验证了该系统在问答准确性方面的显著优势.研究结果显示,基于大模型决策的故障树问答方法不仅有着重要的理论意义,同时在实际应用中也展现出巨大的价值.提供了一种创新的故障树智能问答思路和工具,为未来的研究和开发奠定了坚实的理论基础.
Research on fault tree intelligent question and answering methods based on large model
Fault Tree Question Answering(FTQA)is a form of intelligent question-answering system built upon the fundamentals of fault tree analysis,where enhancing efficiency and accuracy are key challenges.To address this,a novel method based on large model decision-making has been proposed.By transforming the fault tree into a Directed Acyclic Graph(DAG)and integrating deep learning and natural language processing technologies,this method utilizes large decision-making models to develop an intelligent question-answering system.This system is capable of effectively understanding and responding to various questions related to fault trees,thereby solving multiple critical technical challenges.Experiments conducted on various types and sizes of fault tree models have validated the significant advantage of this system in terms of the accuracy of responses.Research findings demonstrate that the fault tree question-answering method based on large model decision-making not only holds significant theoretical implications but also exhibits substantial practical value in application.This introduces an innovative approach and tool for intelligent fault tree question-answearing,laying a solid foundation for future research and development.

Fault treeIntelligent question-answeringAccuracyLarge model decision-making

田云龙、司福东、牛丽、苏明月

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青岛海尔科技有限公司 山东 青岛 266100

数字家庭网络国家工程研究中心 山东 青岛 266100

青岛市智慧家庭交互与控制工程研究中心 山东 青岛 266100

故障树 智能问答 准确性 大模型决策

2024

家电科技
中国家用电器研究院

家电科技

影响因子:0.086
ISSN:1672-0172
年,卷(期):2024.(z1)