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...

תיאור מלא

מידע ביבליוגרפי

Principais autores:	Masoud Karbasi, Mumtaz Ali, Sayed M. Bateni, Changhyun Jun, Mehdi Jamei, Zaher Mundher Yaseen
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Elsevier 2024-01-01
סדרה:	Alexandria Engineering Journal
נושאים:	Pan Evaporation Forecasting Machine Learning Deep Learning Boruta Feature Selection
גישה מקוונת:	http://www.sciencedirect.com/science/article/pii/S1110016823010499
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!