A Hybrid Transformer-CNN Model for Interpolating Meteorological Data on the Tibetan Plateau

High-quality observational data play a crucial role in deepening the investigation of the Tibetan Plateau’s influence on the Asian climate. This study employs eight machine learning models (support vector regression (SVR), k-nearest neighbors (KNN), extreme gradient boosting (XGBoost), random forest...

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Bibliographic Details
Main Authors: Quanzhe Hou, Zhiqiu Gao, Mingxinyu Lu, Yinxin Yu
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Atmosphere
Subjects:
Online Access:https://www.mdpi.com/2073-4433/16/4/431
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