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2012 | OriginalPaper | Buchkapitel

Neural Networks for Time-Series Forecasting

verfasst von : G. Peter Zhang

Erschienen in: Handbook of Natural Computing

Verlag: Springer Berlin Heidelberg

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Abstract

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.

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Titel: Neural Networks for Time-Series Forecasting
verfasst von: G. Peter Zhang
Verlag: Springer Berlin Heidelberg
Buch: Handbook of Natural Computing
Print ISBN: 978-3-540-92909-3

Electronic ISBN: 978-3-540-92910-9

Copyright-Jahr: 2012
DOI: https://doi.org/10.1007/978-3-540-92910-9_14

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