Key
Laboratory of Earth Surface Processes and Regional Response in the
Yangtze-Huaihe River Basin of Anhui Province, Anhui Normal University, School of Geography and Tourism, Wuhu, 241002, China
Engineering Technology Research Center of Resource Environment and
GIS, Wuhu, 241002, China
Key Laboratory of Remote Sensing of
Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou, 730000, China
Zuo Wang
Key
Laboratory of Earth Surface Processes and Regional Response in the
Yangtze-Huaihe River Basin of Anhui Province, Anhui Normal University, School of Geography and Tourism, Wuhu, 241002, China
Key Laboratory of Remote Sensing of
Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou, 730000, China
Ying Zhang
Key Laboratory of Remote Sensing of
Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy
of Sciences, Lanzhou, 730000, China
Peipei Xu
Key
Laboratory of Earth Surface Processes and Regional Response in the
Yangtze-Huaihe River Basin of Anhui Province, Anhui Normal University, School of Geography and Tourism, Wuhu, 241002, China
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Total article views: 3,313 (including HTML, PDF, and XML)
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Total article views: 1,569 (including HTML, PDF, and XML)
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Total article views: 1,744 (including HTML, PDF, and XML)
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
This study aims to investigate the performance of a genetic particle filter which was used as a...
