Efficient prediction of total column ozone based on support vector regression algorithms, numerical models and Suomi-satellite data-Reference-Cited by-同舟云学术

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Efficient prediction of total column ozone based on support vector regression algorithms, numerical models and Suomi-satellite data

Published:2017-01-01 Issue:1 Volume:30 Page:1-10
ISSN:0187-6236
Container-title:Atmósfera
language:
Short-container-title:Atm

Author:

Carro-Calvo Leo, ,Casanova-Mateo Carlos,Sanz-Justo Julia,Casanova-Roque José Luis,Salcedo-Sanz Sancho, , , ,

Publisher

Centro de Ciencias de la Atmosfera

Subject

Atmospheric Science

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Spatial Downscaling of Snow Water Equivalent Using Machine Learning Methods Over the Zayandehroud River Basin, Iran;PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science;2023-07-21

2. Modeling Sulphur Dioxide (SO2) Quality Levels of Jeddah City Using Machine Learning Approaches with Meteorological and Chemical Factors;Sustainability;2022-12-06

3. The Exploration of the Changes In Surface Ozone by Region and Season;Jurnal Kejuruteraan;2022-11-30

4. Makine Öğrenme Algoritmaları ile PM10 Konsantrasyon Tahmini;Journal of Advanced Research in Natural and Applied Sciences;2022-06-15

5. Assessment of Spatio-temporal Climatological trends of ozone over the Indian region using Machine Learning;Spatial Statistics;2021-06

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