The Use of Artificial Intelligence Techniques for Climate Prediction

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: closed (15 December 2023) | Viewed by 259

Special Issue Editors


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Guest Editor
Faculty of Civil Engineering and Architecture, University of Nis, Aleksandra Medvedeva 14, 18000 Nis, Serbia
Interests: hydroinformatics; drought risk analysis; data analysis; artificial intelligence
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Guest Editor
Faculty of Science, Agronomy Department, Hydraulics Division, University 20 Août 1955 Skikda, Route El Hadaik, BP 26, Skikda 21000, Algeria
Interests: machine learning for water resources; water quality; hybrology
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Guest Editor
Department of Railroad Construction and Safety Engineering, Dongyang University, Yeongju 36040, Republic of Korea
Interests: hydrology; water resources; machine learning; data-driven modeling; hydrometeorology; climate change
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Civil Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
Interests: water resources management; hydrological modeling; optimization algorithms; artificial intelligent and machne learning; dam operation
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Special Issue Information

Dear Colleagues,

The application of artificial intelligence techniques can enable new opportunities in climate modeling. Developing innovative and cutting-edge solutions based on the implementation of machine and deep learning approaches can help scientists better understand various climate phenomena.

The primary purpose of this Special Issue is to compile a collection of selected original papers presenting state-of-the-art research on using artificial intelligence techniques for climate prediction. We welcome contributions that emphasize the latest advances on issues such as machine and deep learning approaches to spatiotemporal modeling for different climate phenomena, artificial intelligence for climate applications and the application of machine learning techniques on a climate model output.

Dr. Milan Gocić
Prof. Dr. Salim Heddam
Prof. Dr. Sungwon Kim
Prof. Dr. Ahmed El-Shafie
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • deep learning
  • extreme weather detection
  • climate model output

Published Papers

There is no accepted submissions to this special issue at this moment.
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