Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

Using Random Forests to Select Optimal Input Variables for Short-Term Wind Speed Forecasting Models

Achieving relatively high-accuracy short-term wind speed forecasting estimates is a precondition for the construction and grid-connected operation of wind power forecasting systems for wind farms. Currently, most research is focused on the structure of forecasting models and does not consider the se...

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Bibliographic Details
Main Authors: Hui Wang, Jingxuan Sun, Jianbo Sun, Jilong Wang
Format: Article
Language:English
Published: MDPI AG 2017-10-01
Series:Energies
Subjects:
random forests (RF)
feature selection
input variables selection
kernel-based extreme learning machine
short-term wind speed forecasting
Online Access:https://www.mdpi.com/1996-1073/10/10/1522

Internet

https://www.mdpi.com/1996-1073/10/10/1522

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