Streamflow Data Infilling Using Machine Learning Techniques with Gamma Test
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DOI: 10.1007/s11269-023-03694-8
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- Jenq-Tzong Shiau & Hui-Ting Hsu, 2016. "Suitability of ANN-Based Daily Streamflow Extension Models: a Case Study of Gaoping River Basin, Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1499-1513, March.
- Thakolpat Khampuengson & Wenjia Wang, 2023. "Novel Methods for Imputing Missing Values in Water Level Monitoring Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 851-878, January.
- Jenq-Tzong Shiau & Hui-Ting Hsu, 2016. "Suitability of ANN-Based Daily Streamflow Extension Models: a Case Study of Gaoping River Basin, Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1499-1513, March.
- Tomasz Niedzielski & Michał Halicki, 2023. "Improving Linear Interpolation of Missing Hydrological Data by Applying Integrated Autoregressive Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(14), pages 5707-5724, November.
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Cited by:
- Malihe Danesh & Amin Gharehbaghi & Saeid Mehdizadeh & Amirhossein Danesh, 2025. "A Comparative Assessment of Machine Learning and Deep Learning Models for the Daily River Streamflow Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(4), pages 1911-1930, March.
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Keywords
Data imputation; Recovering missing data; Streamflow prediction; Hybrid model; Evolutionary algorithm; Coxs River;All these keywords.
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