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

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Title:Evaluation Study of Linear Combination Technique for SVM related Time Series Forecasting
Authors:Cheng, Xian
Wu, Ji
Xu, Jin
Keywords:Decision Support for Smart Cities
Decision Analytics, Mobile Services, and Service Science
Time Series Forecasting, SVM, Linear Combination, M3 Competition
Date Issued:08 Jan 2019
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.
Pages/Duration:7 pages
URI:http://hdl.handle.net/10125/59563
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.151
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Decision Support for Smart Cities


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