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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Principais autores:	Masoud Karbasi, Mumtaz Ali, Sayed M. Bateni, Changhyun Jun, Mehdi Jamei, Zaher Mundher Yaseen
格式:	Artigo
語言:	Inglês
出版:	Elsevier 2024-01-01
叢編:	Alexandria Engineering Journal
主題:	Pan Evaporation Forecasting Machine Learning Deep Learning Boruta Feature Selection
在線閱讀:	http://www.sciencedirect.com/science/article/pii/S1110016823010499
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