Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms

The focus of this study is to evaluate the efficacy of Machine Learning (ML) algorithms in the long-lead prediction of El Niño (La Niña) Modoki (ENSO Modoki) index (EMI). We evaluated two widely used non-linear ML algorithms namely Support Vector Regression (SVR) and Random Forest (RF) to forecast t...

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Detalles Bibliográficos
Autores principales: Pal, Manali, Maity, Rajib, Ratnam, J. V., Nonaka, Masami, Behera, Swadhin K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6962158/
https://www.ncbi.nlm.nih.gov/pubmed/31941970
http://dx.doi.org/10.1038/s41598-019-57183-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6962158/
https://www.ncbi.nlm.nih.gov/pubmed/31941970
http://dx.doi.org/10.1038/s41598-019-57183-3

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