水位AI智能预报中的实时数据处理与模型更新方法  

Real Time Data Processing and Model Updating Methods in AI Intelligent Water Level Forecasting

作　　者：李吉涛 LI Jitao(Hubei Hydrological and Water Resources Emergency Monitoring Center,Wuhan,Hubei,430079,China)

机构地区：[1]湖北省水文水资源应急监测中心,湖北武汉430079

出　　处：《智能城市应用》2024年第12期138-141,共4页Smart City Application

摘　　要：水位预报是水资源管理中的重要环节,尤其在防洪、灌溉与水库管理中,准确的水位预测对决策制定至关重要。传统的水位预报方法通常依赖于物理模型和线性假设,但这些方法在应对复杂的水文环境和非线性数据时往往表现不足。随着人工智能(AI)技术的快速发展,尤其是机器学习和深度学习的应用,水位预报的精度和时效性得到了显著提升。AI算法能够通过自动学习历史数据中的规律,克服传统模型的局限,实现对水位变化的高精度预测。同时,实时数据的获取和处理成为提升水位预测系统性能的关键。文中将探讨AI算法在水位预报中的应用,实时数据处理与模型更新方法,及其在实际水文环境中的应用前景。Water level forecasting is an important part of water resource management,especially in flood control,irrigation,and reservoir management.Accurate water level forecasting is crucial for decision-making.Traditional water level forecasting methods often rely on physical models and linear assumptions,but these methods often perform poorly in dealing with complex hydrological environments and nonlinear data.With the rapid development of artificial intelligence(AI)technology,especially the application of machine learning and deep learning,the accuracy and timeliness of water level forecasting have been significantly improved.AI algorithms can overcome the limitations of traditional models and achieve high-precision prediction of water level changes by automatically learning patterns from historical data.Meanwhile,the acquisition and processing of real-time data have become key to improving the performance of water level prediction systems.The article will explore the application of AI algorithms in water level forecasting,real-time data processing and model updating methods,and their prospects in practical hydrological environments.

关 键 词：水位预报 AI算法 实时数据处理 机器学习 模型更新 

分 类 号：TV221[水利工程—水工结构工程]