Enhanced forecasting of multi-step ahead daily soil temperature using advanced hybrid vote algorithm-based tree models

Enhanced forecasting of multi-step ahead daily soil temperature using advanced hybrid vote algorithm-based tree models

In this study, the vote algorithm used to improve the performances of three machine-learning models including M5Prime (M5P), random forest (RF), and random tree (RT) is developed (i.e. V-M5P, V-RF, and V-RT). Developed models were tested for forecasting soil temperature (TS) at 1, 2, and 3 days ahea...

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Bibliographic Details
Main Authors: Javad Hatamiafkoueieh, Salim Heddam, Saeed Khoshtinat, Solmaz Khazaei, Abdol-Baset Osmani, Ebrahim Nohani, Mohammad Kiomarzi, Ehsan Sharafi, John Tiefenbacher
Format: Article
Language:English
Published: IWA Publishing 2023-11-01
Series:Journal of Hydroinformatics
Subjects:
forecasting
m5prime
random forest
random tree
soil temperature
vote
Online Access:http://jhydro.iwaponline.com/content/25/6/2643

Internet

http://jhydro.iwaponline.com/content/25/6/2643

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