Research ArticleOpen accessIn the author namesAn Evolving Autoregressive Predictor for Time Series ForecastingDe Z. Li, Wilson Wang, Fathy IsmailAutoregressive (AR) model is a common predictor that has been extensively used for time series forecasting. Many training methods can used to update AR model parameters, for instance, least square estimate and maximum likelihood estimate; however, both techniques are sensitive to noisy samples and outliers. To deal with the problems, an evolving AR predictor, EAR, is developed in this study … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 1 · 8 Apr 2015 · 6,965 accessesView PDFCite
Research ArticleOpen accessIn the author namesData-Driven Forecasting Schemes: Evaluation and ApplicationsJosip Vrbanek Jr, Wilson WangA reliable multi-step predictor is very useful to a wide array of applications to forecast the behavior of dynamic systems. The objective of this paper is to develop a more robust data-driven predictor for time series forecasting. Based on simulation analysis, it is found that multi-step-ahead forecasting schemes based on step inputs perform better than those based on sequential inputs. … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,565 accessesView PDFCite