Evaluation Study of Linear Combination Technique for SVM related Time Series Forecasting

Date
2019-01-08
Authors
Cheng, Xian
Wu, Ji
Xu, Jin
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Abstract
Time series forecasting and SVM are widely used in many domains, for example, smart city and digital services. Focusing on SVM related time series forecasting model, in this paper we empirical investigate the performance of eight linear combination techniques by using M3 competition dataset which includes 3003 time series. The results reveals that the “forecast combination puzzle” is not exist for combining SVM related forecasting model as the simple average is almost the worst combination technique.
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Decision Support for Smart Cities, Decision Analytics, Mobile Services, and Service Science, Time Series Forecasting, SVM, Linear Combination, M3 Competition
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7 pages
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Proceedings of the 52nd Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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