Machine Learning for the Bias Correction of LDAPS Air Temperature Prediction Model-Reference-Cited by-同舟云学术

Machine Learning for the Bias Correction of LDAPS Air Temperature Prediction Model

Published:2021-04-23 Issue: Volume: Page:
ISSN:
Container-title:2021 6th International Conference on Machine Learning Technologies
language:
Short-container-title:

Author:

Zhang Geer¹

Affiliation:

1. Renmin University of China, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3468891.3468892

Reference14 articles.

1. Dongjin Cho Cheolhee Yoo Jungho Im and Dong-Hyun Cha. 2020. Comparative assessment of various machine learning-based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in urban areas. Earth and Space Science 7 4 (2020) e2019EA000740. Dongjin Cho Cheolhee Yoo Jungho Im and Dong-Hyun Cha. 2020. Comparative assessment of various machine learning-based bias correction methods for numerical weather prediction model forecasts of extreme air temperatures in urban areas. Earth and Space Science 7 4 (2020) e2019EA000740.

2. Climate Modeling; Reports from Ulsan National Institute of Science and Technology (UNIST). 2020. Advance Knowledge in Climate Modeling (Projection of Future Precipitation Change Over South Korea by Regional Climate Models and Bias Correction Methods. Global Warming Focus(2020). Climate Modeling; Reports from Ulsan National Institute of Science and Technology (UNIST). 2020. Advance Knowledge in Climate Modeling (Projection of Future Precipitation Change Over South Korea by Regional Climate Models and Bias Correction Methods. Global Warming Focus(2020).

3. Statistical prediction of the nocturnal urban heat island intensity based on urban morphology and geographical factors - An investigation based on numerical model results for a large ensemble of French cities

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