New hybridization of empirical mode decomposition and least squares support vector machine model in forecasting Malaysia exchange rates

2017 ◽  
Author(s):  
Nur Izzati Abdul Rashid ◽  
Ani Shabri ◽  
Ruhaidah Samsudin
Keyword(s):  
Support Vector Machine ◽  
Exchange Rates ◽  
Least Squares ◽  
Empirical Mode Decomposition ◽  
Support Vector Machine Model ◽  
Support Vector ◽  
Machine Model ◽  
Mode Decomposition

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.

scholarly journals Application of Empirical mode Decomposition with Wavelets Support Vector Machine in time Series Data

2020 ◽  
Vol 9 (3) ◽  
pp. 2451-2454
Keyword(s):  
Support Vector Machine ◽  
Empirical Mode Decomposition ◽  
Support Vector Machine Model ◽  
Time Series Data ◽  
Series Data ◽  
Support Vector ◽  
Machine Model ◽  
Mode Decomposition ◽  
Asean Country ◽  
Wavelet Methods

This paper mainly discussed on the forecast of Thailand tourist visiting Malaysia. This paper proposed a three-stage technique in which the empirical mode decomposition (EMD) is combined with wavelet methods and support vector machine model. We used the proposed technique, EMD_WSVM to forecast two ASEAN country tourism timeseries. Detail experiments are conducted for the proposed method, in which there is a comparison between the EMD_WSVM, WSVM and SVM methods. The proposed EMD_WSVM model is determined to be dominant to the other methods in predicting the number of tourist arrivals

Accuracy improvement of iron ore analysis using laser-induced breakdown spectroscopy with a hybrid sparse partial least squares and least-squares support vector machine model

2018 ◽  
Vol 33 (8) ◽  
pp. 1330-1335 ◽  
Author(s):  
Y. M. Guo ◽  
L. B. Guo ◽  
Z. Q. Hao ◽  
Y. Tang ◽  
S. X. Ma ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Partial Least Squares ◽  
Iron Ore ◽  
Support Vector Machine Model ◽  
Support Vector ◽  
Accuracy Improvement ◽  
Machine Model ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

A hybrid sparse partial least squares and least-squares support vector machine model was proposed to improve the accuracy of iron ore analysis using LIBS.

A mixed effects least squares support vector machine model for classification of longitudinal data

2012 ◽  
Vol 56 (3) ◽  
pp. 611-628 ◽  
Author(s):  
Jan Luts ◽  
Geert Molenberghs ◽  
Geert Verbeke ◽  
Sabine Van Huffel ◽  
Johan A.K. Suykens
Keyword(s):  
Support Vector Machine ◽  
Longitudinal Data ◽  
Least Squares ◽  
Support Vector Machine Model ◽  
Mixed Effects ◽  
Support Vector ◽  
Machine Model

scholarly journals Correction: Accuracy improvement of iron ore analysis using laser-induced breakdown spectroscopy with a hybrid sparse partial least squares and least-squares support vector machine model

2020 ◽  
Vol 35 (7) ◽  
pp. 1487-1487
Author(s):  
Y. M. Guo ◽  
L. B. Guo ◽  
Z. Q. Hao ◽  
Y. Tang ◽  
S. X. Ma ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
Iron Ore ◽  
Support Vector Machine Model ◽  
Laser Induced Breakdown Spectroscopy ◽  
Support Vector ◽  
Accuracy Improvement ◽  
Machine Model ◽  
Breakdown Spectroscopy ◽  
Laser Induced Breakdown

Correction for ‘Accuracy improvement of iron ore analysis using laser-induced breakdown spectroscopy with a hybrid sparse partial least squares and least-squares support vector machine model’ by Y. M. Guo et al., J. Anal. At. Spectrom., 2018, 33, 1330–1335, DOI: 10.1039/C8JA00119G.

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