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

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.