An innovative one-class least squares support vector machine model based on continuous cognition

2017 ◽  
Vol 123 ◽  
pp. 217-228 ◽  
Author(s):  
Guangzao Huang ◽  
Zijiang Yang ◽  
Xiaojing Chen ◽  
Guoli Ji
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Support Vector Machine Model ◽  
Support Vector ◽  
Machine Model ◽  
Model Based

scholarly journals A Hybrid Least Square Support Vector Machine Model with Parameters Optimization for Stock Forecasting

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Jian Chai ◽  
Jiangze Du ◽  
Kin Keung Lai ◽  
Yan Pui Lee
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Support Vector Machine Model ◽  
Optimization Methods ◽  
Parameters Optimization ◽  
Least Square ◽  
Movement Direction ◽  
Support Vector ◽  
Machine Model ◽  
Mode Decomposition

This paper proposes an EMD-LSSVM (empirical mode decomposition least squares support vector machine) model to analyze the CSI 300 index. A WD-LSSVM (wavelet denoising least squares support machine) is also proposed as a benchmark to compare with the performance of EMD-LSSVM. Since parameters selection is vital to the performance of the model, different optimization methods are used, including simplex, GS (grid search), PSO (particle swarm optimization), and GA (genetic algorithm). Experimental results show that the EMD-LSSVM model with GS algorithm outperforms other methods in predicting stock market movement direction.

A Support Vector Machine Model based on Mixed Time Series Prediction

2021 ◽  
Author(s):  
Meixia Wang ◽  
Yuan Lei ◽  
Yuni Liang ◽  
Xuejing Lv ◽  
Weipeng Mo
Keyword(s):  
Time Series ◽  
Support Vector Machine ◽  
Support Vector Machine Model ◽  
Time Series Prediction ◽  
Support Vector ◽  
Machine Model ◽  
Model Based
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