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
Authors | Liu, Chan-Juan, Xu, Jing, Li, Xi-An, Yu, Zhongyao and Wu, Jinran |
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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. |
Keywords | Water forecasting; Machine learning/deep learning; Web of Science ; Visualization |
Year | 01 Jan 2024 |
Journal | Artificial Intelligence in Geosciences |
Journal citation | 5, pp. 1-12 |
Publisher | Elsevier Ltd. (UK) - Pergamon Press |
ISSN | 2666-5441 |
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 access | Open access |
Research or scholarly | Research |
Page range | 1-12 |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication process dates | |
Deposited | 21 Nov 2024 |
Additional information | © 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 publication | China |
https://acuresearchbank.acu.edu.au/item/9113q/water-resource-forecasting-with-machine-learning-and-deep-learning-a-scientometric-analysis
Download files
Publisher's version
OA_2024_Water_resource_forecasting_with_machine_learning.pdf | |
License: CC BY-NC-ND 4.0 | |
File access level: Open |
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