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http://hdl.handle.net/10125/59563
Evaluation Study of Linear Combination Technique for SVM related Time Series Forecasting
Item Summary
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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