Neural networks has become an important method for time series forecasting. There is increasing interest in using neural networks to model and forecast time series. This chapter provides a review of some recent developments in time series forecasting with neural networks, a brief description of neural networks, their advantages over traditional forecasting models, and some recent applications. Several important data and modeling issues for time series forecasting are highlighted. In addition, recent developments in several methodological areas such as seasonal time series modeling, multi-period forecasting, and the ensemble method are reviewed.
CITATION STYLE
Zhang, G. P. (2012). Neural networks for time-series forecasting. In Handbook of Natural Computing (Vol. 1–4, pp. 461–477). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-92910-9_14
Mendeley helps you to discover research relevant for your work.