Twin Least Square Support Vector Regression Model Based on Gauss-Laplace Mixed Noise Feature with Its Application in Wind Speed Prediction
In this article, it was observed that the noise in some real-world applications, such as wind<br />power forecasting and direction of the arrival estimation problem, does not satisfy the single noise<br />distribution, including Gaussian distribution and Laplace distribution, but the mix...
Main Authors: | Shiguang Zhang, Chao Liu, Wei Wang, Baofang Chang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-09-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/22/10/1102 |
Similar Items
-
Twin Least Squares Support Vector Regression of Heteroscedastic Gaussian Noise Model
by: Shiguang Zhang, et al.
Published: (2020-01-01) -
<i>ν</i>-Support Vector Regression Model Based on Gauss-Laplace Mixture Noise Characteristic for Wind Speed Prediction
by: Shiguang Zhang, et al.
Published: (2019-10-01) -
Newton-Gauss Algorithm of Robust Weighted Total Least Squares Model
by: WANG Bin, et al.
Published: (2015-06-01) -
Incremental Reduced Least Squares Twin Support Vector Regression
by: CAO Jie, GU Binjie, XIONG Weili, PAN Feng
Published: (2021-03-01) -
An effective Weighted Multi-class Least Squares Twin Support Vector Machine for Imbalanced data classification
by: Divya Tomar, et al.
Published: (2015-08-01)