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DeepSeek-R1模型在防汛智能推理中的应用探索研究

吕凯 师鹏飞 肖家清 张正一 邱子骏 林斌

水利学报2026,Vol.57Issue(6):835-846,860,13.
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水利学报2026,Vol.57Issue(6):835-846,860,13.DOI:10.3724/j.slxb.20250408

DeepSeek-R1模型在防汛智能推理中的应用探索研究

Research on the application of the DeepSeek-R1 model in intelligent flood prevention Reasoning

吕凯 1师鹏飞 2肖家清 1张正一 1邱子骏 1林斌3

作者信息

  • 1. 河海大学水灾害防御全国重点实验室,江苏南京 210098||河海大学水文水资源学院,江苏南京 210098
  • 2. 河海大学水灾害防御全国重点实验室,江苏南京 210098||河海大学水文水资源学院,江苏南京 210098||洪涝灾害风险预警与防控应急管理部重点实验室,江苏南京 210098
  • 3. 福建省水利水电勘测设计研究院有限公司,福建 福州 350000
  • 折叠

摘要

Abstract

The development of generative AI models offers a new research paradigm for hydrological sciences.This paper takes DeepSeek-R 1 as a representative of generative AI model and,based on the actual needs of flood control activities,explores its application potential,current limitations,and future prospects in intelligent flood prevention reasoning through two typical operational scenarios:the reasoning of rainfall-runoff process and the intelligent and rapid recommendation of flood prevent scheduling schemes.The research results show that the DeepSeek-R 1 model can effectively combine mechanistic background knowledge with sample data in the rainfall-runoff process reasoning task,learn the mapping characteristics between watershed rainfall-runoff data and the upstream and downstream river discharge data,and perform reasoning on the runoff process under new scenarios.Regarding the intelligent rapid recommendation of flood control scheduling schemes,DeepSeek-R 1 exhibits good capabilities in demand understanding and parsing.It can efficiently integrate multi-source information,analyze complex scheduling needs,quickly identify spatio-temporal mapping relationships among rainfall,hydrological,and condition data,and per-form result reasoning and regulation scheme recommendations for new rainfall scenarios.The DeepSeek-R 1 model is essentially a probabilistic generative model,as opposed to a physics-based mechanistic model.Its predictive capabili-ties are grounded in the correlation analysis between data and built-in knowledge,rather than physical equation cal-culations or big data fitting.Therefore,its effectiveness in specialized fields is significantly correlated with the train-ing process,requiring parameter fine-tuning with professional data to enhance its adaptability in the field of flood pre-vention.This research findings provide a technical pathway and case reference for exploring the application of genera-tive AI models in intelligent flood prevention reasoning.

关键词

生成式人工智能模型/DeepSeek-R1/防汛智能推理

Key words

generative AI model/DeepSeek-R1/intelligent flood prevention reasoning

分类

建筑与水利

引用本文复制引用

吕凯,师鹏飞,肖家清,张正一,邱子骏,林斌..DeepSeek-R1模型在防汛智能推理中的应用探索研究[J].水利学报,2026,57(6):835-846,860,13.

基金项目

国家自然科学基金项目(52279009) (52279009)

水利学报

0559-9350

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