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Connectionist approach to time series prediction: an empirical test
Authors:Ramesh Sharda  Rajendra B. Patil
Affiliation:(1) Oklahoma State University, 74078-0555 Stillwater, Oklahoma, USA;(2) Department of Computer Science, New Mexico State University, 88003 Las Cruces, NM, USA
Abstract:Among the various potential applications of neural networks, forecasting is considered to be a major application. Several researchers have reported their experiences with the use of neural networks in forecasting, and the evidence is inconclusive. This paper presents the results of a forecasting competition between a neural network model and a Box-Jenkins automatic forecasting expert system. Seventy-five series, a subset of data series which have been used for comparison of various forecasting techniques, were analysed using the Box-Jenkins approach and a neural network implementation. The results show that the simple neural net model tested on this set of time series could forecast about as well as the Box-Jenkins forecasting system.
Keywords:Forecasting  time-series  neural networks  connectionist expert systems  back propagation applications
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