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Wind power prediction using bootstrap aggregating trees approach to enabling sustainable wind power integration in a smart grid
Fouzi Harrou, Ahmed Saidi,
Ying Sun
Computer, Electrical and Mathematical Sciences and Engineering
Statistics
Research output
:
Contribution to journal
›
Article
›
peer-review
39
Scopus citations
Overview
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Earth and Planetary Sciences
Wind Power
100%
Approach
66%
Model
66%
Prediction
66%
Regression
66%
Smart Grid
33%
Investigation
16%
Ability
16%
Increasing
16%
Error
16%
Need
16%
Coefficient
16%
Tool
16%
Selection
16%
Mathematics
Forecasting
66%
Linear Regression
66%
Regression
66%
Bagged Tree
50%
Support Vector Machine
33%
Principal Component
33%
Partial Least Squares
33%
Trees
33%
Regressors
16%
Prediction Method
16%
Prediction Quality
16%
Kernel
16%
Bootstrapping
16%
Computer Science
Smart Grid
66%
Simulation Mode
66%
Regression
66%
Prediction Performance
33%
Principal Component
33%
Support Vector Regression
33%
Least Squares Methods
16%
Anomaly-Based Detection
16%
Gaussian Kernel
16%
Term Prediction
16%
Decision Tree Approach
16%
Economics, Econometrics and Finance
Principal Components
33%