Daily reference evapotranspiration prediction of Tieguanyin tea plants based on mathematical morphology clustering and improved generalized regression neural network
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DOI: 10.1016/j.agwat.2020.106177
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Cited by:
- Valipour, Mohammad & Khoshkam, Helaleh & Bateni, Sayed M. & Jun, Changhyun & Band, Shahab S., 2023. "Hybrid machine learning and deep learning models for multi-step-ahead daily reference evapotranspiration forecasting in different climate regions across the contiguous United States," Agricultural Water Management, Elsevier, vol. 283(C).
- Hadeel E. Khairan & Salah L. Zubaidi & Mustafa Al-Mukhtar & Anmar Dulaimi & Hussein Al-Bugharbee & Furat A. Al-Faraj & Hussein Mohammed Ridha, 2023. "Assessing the Potential of Hybrid-Based Metaheuristic Algorithms Integrated with ANNs for Accurate Reference Evapotranspiration Forecasting," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
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Keywords
Tieguanyin tea plant; Daily reference evapotranspiration; Generalized regression neural network; Mathematical morphology clustering; Prediction;All these keywords.
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