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...
Saved in:
| Main Authors: | Ting Zhou, Shiguang Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10945315/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
<italic>CompoHyDen:</italic> Hyperspectral Image Restoration via Nonconvex Componentwise Minimization
by: Hazique Aetesam, et al.
Published: (2024-01-01) -
A Noise Reduction Method for Photoacoustic Imaging <italic>In Vivo</italic> Based on EMD and Conditional Mutual Information
by: Meng Zhou, et al.
Published: (2019-01-01) -
How to Design a Differential CMOS <italic>LC</italic> Oscillator
by: Asad A. Abidi, et al.
Published: (2025-01-01) -
Twin Support Vector Regression Model Based on Heteroscedastic Gaussian Noise and Its Application
by: Shiguang Zhang, et al.
Published: (2022-01-01) -
Robust Regression as a Sensible Alternative to the Weighted Ordinary Least Squares Regression in case of Heteroskedasticity. A Tutorial
by: Annalisa Orenti, et al.
Published: (2024-10-01)