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Article Details
- Journal Title
- Advances in Meteorology
- Volume
- 2019
- Article Title
- Assessing the Applicability of Random Forest, Stochastic Gradient Boosted Model, and Extreme Learning Machine Methods to the Quantitative Precipitation Estimation of the Radar Data: A Case Study to Gwangdeoksan Radar, South Korea, in 2018
- List of Authors
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- Ju-Young Shin(ORCID ID: https://orcid.org/0000-0002-1520-3965)
- Joo-Wan Cha
- Kyu-Rang Kim
- Jong-Chul Ha
- Article ID
- 6542410
- Article Type
- Research Article
- No. of Pages
- 17 Pages
- Additional Authors
Invoice Details
- Invoice Issue Date
- 29 March 2024
- Type of Reprints
- Colored, Covered
- Invoice Ref. No.
- Terms
- Payable upon Receipt
Charges
- No. of Copies
- Reprints Charges
- 0.00
- Total
- $