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European Symposium on Time Series Prediction:
Special Issue
Amaury Lendasse, Timo Honkela and Olli Simula
Neurocomputing
2010.
AbstractTime series forecasting is a challenge in many fields. In finance, one
forecasts stock exchange courses or stock market indices; data processing
specialists forecast the flow of information on their networks; producers of
electricity forecast the load of the following day. The common point to their
problems is the following: how can one analyze and use the past to predict
the future? Many techniques exist including linear methods such as ARX
or ARMA, and nonlinear ones such as the ones used in the area of machine
learning [1]. [Edit]
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