Water resource forecasting with machine learning and deep learning : A scientometric analysis

Journal article

Liu, Chan-Juan, Xu, Jing, Li, Xi-An, Yu, Zhongyao and Wu, Jinran. (2024). Water resource forecasting with machine learning and deep learning : A scientometric analysis. Artificial Intelligence in Geosciences. 5, pp. 1-12. https://doi.org/10.1016/j.aiig.2024.100084
AuthorsLiu, Chan-Juan, Xu, Jing, Li, Xi-An, Yu, Zhongyao and Wu, Jinran
Abstract

Water prediction plays a crucial role in modern-day water resource management, encompassing both hydrological 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.

KeywordsWater forecasting; Machine learning/deep learning; Web of Science ; Visualization
Year01 Jan 2024
JournalArtificial Intelligence in Geosciences
Journal citation5, pp. 1-12
PublisherElsevier Ltd. (UK) - Pergamon Press
ISSN2666-5441
Digital Object Identifier (DOI)https://doi.org/10.1016/j.aiig.2024.100084
Web address (URL)https://www.sciencedirect.com/science/article/pii/S266654412400025X?via%3Dihub
Open accessOpen access
Research or scholarlyResearch
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Deposited21 Nov 2024
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© 2024 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Place of publicationChina
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