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The K.U.Leuven competition data: a challenge for advanced neural network techniques

8 years 11 months ago
The K.U.Leuven competition data: a challenge for advanced neural network techniques
In this paper we shortly discuss the K.U. Leuven time-series prediction competition, which has been held in the framework of the International Workshop on Advanced Black-Box Techniques for Nonlinear Modeling, K.U.Leuven Belgium July 8-10 1998. The data are related to a 5-scroll attractor, generated from a generalized Chua's circuit. The time-series consists of a given set of 2000 data points, where the next 200 points are to be predicted. In total, 17 entries have been submitted. The winning contribution by McNames succeeds in making an accurate prediction over a time horizon of about 300 points using a nearest trajectory method, which incorporates local modeling and cross-validation techniques. The competition data can serve as a challenging test-case for adv anced nonlinear modelling techniques, including neural netw orks. The data are able to reveal shortcomings of many methods. Keywords. Time-series prediction, generalized Chua's circuit, chaos.
Johan A. K. Suykens, Joos Vandewalle
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 2000
Where ESANN
Authors Johan A. K. Suykens, Joos Vandewalle
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