A quadratic penalty item optimal variational mode decomposition method based on single-objective salp swarm algorithm

2020 ◽  
Vol 138 ◽  
pp. 106567 ◽  
Author(s):  
Xinlong Zhao ◽  
Pengfei Wu ◽  
Xiuxing Yin
Keyword(s):  
Decomposition Method ◽  
Variational Mode Decomposition ◽  
Salp Swarm Algorithm ◽  
Mode Decomposition ◽  
Swarm Algorithm ◽  
Single Objective

scholarly journals Short-term wind power prediction based on hybrid variational mode decomposition and least squares support vector machine optimized by improved salp swarm algorithm model

2021 ◽  
Vol 2125 (1) ◽  
pp. 012012
Author(s):  
Zhongde Su ◽  
Huacai Lu
Keyword(s):  
Support Vector Machine ◽  
Wind Power ◽  
Support Vector ◽  
Variational Mode Decomposition ◽  
Power Prediction ◽  
Short Term ◽  
Salp Swarm Algorithm ◽  
Mode Decomposition ◽  
Wind Power Prediction ◽  
Swarm Algorithm

Abstract To improve the accuracy of wind power prediction, a short-term wind power prediction model based on variational mode decomposition (VMD) and improved salp swarm algorithm (ISSA) optimized least squares support vector machine (LSSVM) is proposed. In the model, the variational modal decomposition is used to decompose the wind power sequence into multiple eigenmode components with limited bandwidth. The improved salp swarm algorithm is employed to tune the regularization parameter and kernel parameter in LSSVM. The proposed wind power prediction strategy using mean one-hour historical wind power data collected from a wind farm located in zhejiang, China. Compared with other prediction models illustrate the better prediction performance of VMD-ISSA-LSSVM.

Sign in / Sign up

Export Citation Format

Share Document