Proximal <italic>LSSVR</italic> of Gauss-Laplacian With Mixed-Noise-Characteristics and Its Applications for Short-Term Wind-Speed Forecasting

Proximal <italic>LSSVR</italic> of Gauss-Laplacian With Mixed-Noise-Characteristics and Its Applications for Short-Term Wind-Speed Forecasting

Proximal least squares support vector regression (PLSSVR) is a novel regression machine that combines the advantages of proximal support vector regression (PSVR) and least squares support vector regression (LSSVR). It possesses the traits of high efficiency, simplicity, and good generalization abili...

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Bibliographic Details
Main Authors: Ting Zhou, Shiguang Zhang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Heteroscedastic gauss-laplacian noise
least squares support vector regression
mixed-noise-characteristics
proximal model
wind-speed forecasting
Online Access:https://ieeexplore.ieee.org/document/10945315/
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