The practical foundation,current application status,and future prospects for the integration of machine learning in empowering intelligent water conservancy
The practical foundation,current application status,and future prospects for the integration of machine learning in empowering intelligent water conservancy
[Objective]To provide a comprehensive overview of the applications and developments of machine learning in smart water management,this article thoroughly reviews relevant research both domestically and internationally.[Methods]Through comparative analysis and summarization,it elucidates the practical foundation,current applications,and future prospects of ma-chine learning in advancing the intelligence of the water management industry.[Results]Machine learning has been extensively applied in scenarios such as water resource supply and demand forecasting,optimization of scheduling,water disaster risk man-agement and flood control,water quality monitoring and forecasting,as well as hydrological process simulation and prediction.Among these,neural networks are the most commonly used machine learning algorithm,and water quality monitoring and forecas-ting constitute the primary application fields.In the future,machine learning will enhance the"prediction-early warning-preven-tion-contingency plan"functionalities of smart water management by improving prediction models,optimizing early warning sys-tems,conducting retrospective root cause analyses,and aiding in contingency planning.These advancements will expedite the construction of water resource management and allocation application systems,thereby enhancing the efficiency and scientific nature of decision-making in the water management industry.[Conclusion]This article serves as a comprehensive and in-depth technical reference for scholars in related fields.
关键词
机器学习/人工智能算法/智慧水利/数据驱动/水资源/水质
Key words
machine learning/artificial intelligence algorithm/smart water management/data driven/water resources/water quality
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