Machine Learning for Ocean Modelling
Ocean science, as a form of quantitative intelligence, is a systematic enterprise that creates knowledge and builds models from reproducible sea experiments and testable predictions. The nascent explosion of artificial intelligence methods, from dynamic Bayesian inference to deep learning, provides an unprecedented opportunity to help ocean modelers analyze data and accelerate scientific progress by extracting new knowledge and models. This special issue is interested in studies that provide important new developments in all aspects of machine learning for ocean modelling, from new learning theory, methods, and architectures to the implementation of existing schemes to ocean modelling.
The journal's submission platform (https://www.editorialmanager.com/ocemod/default.aspx) is available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript and select the article type of “VSI:Machine Learning” when submitting your manuscript online.
For more information, see the attachment and this link:
https://www.sciencedirect.com/journal/o ... -modelling
Thank you,
The Guest Editors
Special Issue - Machine Learning for Ocean Modelling
Special Issue - Machine Learning for Ocean Modelling
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