Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/104971
Type: Artigo de evento
Title: Long-term Time Series Prediction Using Wrappers For Variable Selection And Clustering For Data Partition
Author: Puma-Villanueva W.J.
Dos Santos E.P.
Von Zuben F.J.
Abstract: In an attempt to implement long-term time series prediction based on the recursive application of a one-step-ahead multilayer neural network predictor, we have considered the eleven short time series provided by the organizers of the Special Session NN3 Neural Network Forecasting Competition, and have proposed a joint application of a variable selection technique and a clustering procedure. The purpose was to define unbiased partition subsets and predictors with high generalization capability, based on a wrapper methodology. The proposed approach overcomes the performance of the predictor that considers all the lags in the regression vector. After obtaining the eleven long-term predictors, we conclude the paper presenting the eighteen multi-step predictions for each time series, as requested in the competition. ©2007 IEEE.
Editor: 
Rights: fechado
Identifier DOI: 10.1109/IJCNN.2007.4371450
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-51749092208&partnerID=40&md5=6d0f44b67de45512f90250d554040c7d
Date Issue: 2007
Appears in Collections:Unicamp - Artigos e Outros Documentos

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