A weighted LS-SVM based learning system for time series forecasting

DOI10.1016/j.ins.2014.12.031zbMath1360.68667OpenAlexW2010680143MaRDI QIDQ528700

Shie-Jue Lee, Thao-Tsen Chen

Publication date: 16 May 2017

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2014.12.031

zbMATH Keywords

mutual informationtime series forecastingsupport vector machinenearest neighbormulti-step forecasting

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

Shape constrained risk-neutral density estimation by support vector regression ⋮ Root mean square error or mean absolute error? Use their ratio as well ⋮ Wavelet-denoising multiple echo state networks for multivariate time series prediction

Cites Work

• Time series forecasting using a hybrid ARIMA and neural network model
• Interval type-2 fuzzy weight adjustment for backpropagation neural networks with application in time series prediction
• Fuzzy time series and its models
• Weighted least squares support vector machines: robustness and sparse approximation
• Modified support vector machines in financial time series forecasting
• Mutual information functions versus correlation functions.
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: A weighted LS-SVM based learning system for time series forecasting