Articles | Volume 18, issue 3
https://doi.org/10.5194/amt-18-737-2025
https://doi.org/10.5194/amt-18-737-2025
Research article
 | 
10 Feb 2025
Research article |  | 10 Feb 2025

A quality control method based on physical constraints and data-driven collaborative artificial intelligence for wind observations along high-speed railway lines

Xiong Xiong, Jiajun Chen, Yanchao Zhang, Xin Chen, Yingchao Zhang, and Xiaoling Ye

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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Cited articles

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This study introduces a novel quality control method, physical constraints and data-driven collaborative artificial intelligence (PD-BX), aimed at reducing wind speed measurement errors caused by the complex environments surrounding high-speed railway lines, thereby enhancing the accuracy and reliability of measurements.

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