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Authors
Zuo, Hui-Min
Qiu, Jun
Li, Fang-Fang
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Funding
Funding for this research was provided by:
the Key R&D program of Science and Technology Department of Tibet (XZ202101ZY0003G)
National Natural Science Foundation of China (U2340210, 91847302, 51979276)
Open Research Fund Program of State key Laboratory of Hydroscience and Engineering (sklhse-2021-B-06)
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Article History
Received: 8 December 2023
Accepted: 24 April 2024
First Online: 23 May 2024
Declarations
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: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
: 1. A new CCM method is proposed to induce computational complexity with the assistance of PSO.2. A detailed comparative analysis is conducted on the impact of two extrapolation strategies on cloud prediction.3. For fast-moving cloud, both CCM and the proposed PSO-CCM is more accurate than the persistence prediction for short-term cloud motion.
