水位预测的机器学习方法  

Machine Learning Approaches for Water Level Prediction

作　　者：张树波[1] 

机构地区：[1]广州航海学院计算机系,广东 广州

出　　处：《人工智能与机器人研究》2025年第2期290-303,共14页Artificial Intelligence and Robotics Research

摘　　要：水是所有生命的物质基础,与人类的生活、生产息息相关,水资源的开发和利用对生活生产、生态环境和社会经济发展具有重要的影响。研究水位动态变化规律以及提前预测水位,对于水资源的开发利用、湿地保护、防洪减灾、船舶配载和安全通航等具有重要的现实意义。水位的高低受到天气、水文等各种复杂因素的影响,水位预测是水文、气象、航道和海事等部门关注的难题和研究热点。本文对近年来机器学习方法在水位预测方面的研究进展和所取得的成果进行分析和评述,分析了现有方法存在的问题和面临的挑战,指出水位预测未来的主要研究方向。Water is the basis for all life and is closely related to human life and production. The development and utilization of water resources have a significant impact on life, production, ecological environment, and social and economic development. Investigating the dynamic patterns of water level changes and forecasting water levels ahead of time are of great practical importance. They play a crucial role in multiple aspects, such as the exploitation and utilization of water resources, the conservation of wetlands, the prevention of floods and reduction of disasters, the loading arrangements of ships, and the guarantee of safe navigation. The water level is affected by various complex factors such as weather and hydrology. The prediction of water level is a difficult thing concerned by departments such as hydrology, meteorology, etc. hence it has become the research focuses in the past years. In this paper, various machine learning algorithms used for predicting water level are reviewed and commented, and the challenge that researchers in this field faced is then pointed out, in the end, the perspectives in this realm are also proposed.

关 键 词：水位预测 机器学习 时间序列 特征提取 

分 类 号：P332[天文地球—水文科学]