Water prediction plays a crucial role in modern-day water resource management,encompassing both logical hydro-patterns and demand forecasts.To gain insights into its current focus,status,and emerging themes,this study...Water prediction plays a crucial role in modern-day water resource management,encompassing both logical hydro-patterns and demand forecasts.To gain insights into its current focus,status,and emerging themes,this study analyzed 876 articles published between 2015 and 2022,retrieved from the Web of Science database.Leveraging CiteSpace visualization software,bibliometric techniques,and literature review methodologies,the investigation identified essential literature related to water prediction using machine learning and deep learning approaches.Through a comprehensive analysis,the study identified significant countries,institutions,authors,journals,and keywords in this field.By exploring this data,the research mapped out prevailing trends and cutting-edge areas,providing valuable insights for researchers and practitioners involved in water prediction through machine learning and deep learning.The study aims to guide future inquiries by highlighting key research domains and emerging areas of interest.展开更多
基金The funding for this study was provided by the Ministry of Ed-ucation of Humanities and Social Science project in China (Project No.22YJC630083)the 2022 Shanghai Chenguang Scholars Program (Project No.22CGA82)+1 种基金the Belt and Road Special Foundation of The National Key Laboratory of Water Disaster Prevention (2021491811)the National Social Science Fund of China (Project No.23CGL077).
文摘Water prediction plays a crucial role in modern-day water resource management,encompassing both logical hydro-patterns and demand forecasts.To gain insights into its current focus,status,and emerging themes,this study analyzed 876 articles published between 2015 and 2022,retrieved from the Web of Science database.Leveraging CiteSpace visualization software,bibliometric techniques,and literature review methodologies,the investigation identified essential literature related to water prediction using machine learning and deep learning approaches.Through a comprehensive analysis,the study identified significant countries,institutions,authors,journals,and keywords in this field.By exploring this data,the research mapped out prevailing trends and cutting-edge areas,providing valuable insights for researchers and practitioners involved in water prediction through machine learning and deep learning.The study aims to guide future inquiries by highlighting key research domains and emerging areas of interest.
