Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition

In this study, two deep learning approaches, bidirectional long short-term memory (BiLSTM) and long short-term memory (LSTM), were used along with adaptive boosting and general regression neural network to forecast multi-step-ahead pan evaporation in two arid climate stations in Iran (Ahvaz and Yazd...

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Bibliografische Detailangaben

Hauptverfasser:	Masoud Karbasi, Mumtaz Ali, Sayed M. Bateni, Changhyun Jun, Mehdi Jamei, Zaher Mundher Yaseen
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2024-01-01
Schriftenreihe:	Alexandria Engineering Journal
Schlagworte:	Pan Evaporation Forecasting Machine Learning Deep Learning Boruta Feature Selection
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S1110016823010499
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