中国水利Issue(5)：29-36,8.DOI:10.3969/j.issn.1000-1123.2025.05.003
大语言模型发展研究及其在防洪"四预"平台智能交互的应用探讨
Development of large language models and their application in intelligent interaction on the"four pres"platform
摘要
Abstract
Large language models(LLMs)have emerged as a significant breakthrough in artificial intelligence in recent years.Leveraging the Transformer architecture and self-attention mechanisms,these models exhibit near-human natural language understanding capabilities at an ultra-large scale,assisting human cognition,reasoning,judgment,and decision-making.Currently,the application of LLMs in specialized domains has become a focal point,especially with the open-source release of DeepSeek based on the Mixture of Experts(MOE)architecture,which offers a more accessible technical pathway for industry applications and further stimulates related research.The"four pres"(forecasting,early warning,pre-planning,and emergency response)in flood control represent a novel intelligent business application in water conservancy based on digital twin technology.This system is characterized by strong specialization,lengthy business chains,and complex system architecture.While functionally comprehensive,there remains room for improvement in usability.Based on an analysis of the understanding and reasoning capabilities of large language models,this study proposes,for the first time,a classification system for intelligent interaction with large models,ranging from L0 to L3 levels.Focusing on intent recognition and intelligent invocation,the research explores application scenarios and technical implementation paths that support the"four pres"platform.Methods to enhance the output certainty of large models are proposed by optimizing"preset content"and incorporating specific problem overlays,which are tested on general large models.The study also explores pathways for large models to intelligently invoke professional models within the"four pres"platform,providing feasible solutions to improve interactive friendliness.Additionally,this research offers valuable references for the deep application of large language models in intelligent water conservancy business.关键词
大语言模型/ChatGPT/DeepSeek/防洪"四预"/意图识别/模型驱动/垂直领域大模型/专业小模型Key words
large language models(LLMs)/ChatGPT/DeepSeek/"four pres"in flood control/intent recognition/model-driven/vertical domain large models/specialized small models分类
水利科学引用本文复制引用
郭磊,冯钧,直伟,周思源..大语言模型发展研究及其在防洪"四预"平台智能交互的应用探讨[J].中国水利,2025,(5):29-36,8.基金项目
广东省水利科技创新项目"广东省大中型水库汛期水位动态控制与洪水资源安全利用关键技术研究". （）
