Modeling Of Mean Tropospheric Temperature From Convolutional Neural Networks
Author:
Affiliation:
1. VIZLAB—X-Reality and Geoinformatics Laboratory, UNISINOS,Sao Leopoldo,RS,Brazil
2. Institute of Geography, Federal University of Uberlandia,Monte Carmelo,MG,Brazil
3. Brazilian Institute of Space Research (INPE),Cachoeira Paulista,SP,Brazil
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282413.pdf?arnumber=10282413
Reference11 articles.
1. Improving the Estimation of Weighted Mean Temperature in China Using Machine Learning Methods
2. Evaluation of Modeling Water-Vapor-Weighted Mean Tropospheric Temperature for GNSS-Integrated Water Vapor Estimates in Brazil
3. Advanced Grid Model of Weighted Mean Temperature Based on Feedforward Neural Network Over China;zhu;Earth and Space Science,2020
4. Forecasting GNSS Zenith Troposphere Delay by Improving GPT3 Model with Machine Learning in Antarctica;li;Atmosphere,2021
5. Monitoring precipitable water vapor in real-time using global navigation satellite systems
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