A hybrid approach for regionalization of precipitation based on maximal discrete wavelet transform and growing neural gas network clustering
- DOI
- 10.1038/s41598-025-24400-1
- Published
- 2025-11-18
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-24400-1,
title = {A hybrid approach for regionalization of precipitation based on maximal discrete wavelet transform and growing neural gas network clustering},
author = {Xu Tao and Ma Ben and He Cao Yin Xuan and Ali Arshaghi},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-24400-1},
url = {https://doi.org/10.1038/s41598-025-24400-1}
}RIS
TY - JOUR TI - A hybrid approach for regionalization of precipitation based on maximal discrete wavelet transform and growing neural gas network clustering AU - Xu Tao AU - Ma Ben AU - He Cao Yin Xuan AU - Ali Arshaghi PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-24400-1 UR - https://doi.org/10.1038/s41598-025-24400-1 ER -
APA
Tao, X., Ben, M., Xuan, H. C. Y., & Arshaghi, A. (2025). A hybrid approach for regionalization of precipitation based on maximal discrete wavelet transform and growing neural gas network clustering. Scientific Reports. https://doi.org/10.1038/s41598-025-24400-1
Source records
- crossref · retrieved 2026-09-26T06:31:52.961Z