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Pesquisa Operacional

versão impressa ISSN 0101-7438versão On-line ISSN 1678-5142

Resumo

MELO, Brício de; MILIONI, Armando Zeferino  e  NASCIMENTO JUNIOR, Cairo Lucio. Daily and monthly sugar price forecasting using the mixture of local expert models. Pesqui. Oper. [online]. 2007, vol.27, n.2, pp.235-246. ISSN 0101-7438.  https://doi.org/10.1590/S0101-74382007000200003.

This article concerns the application of the Mixture of Local Expert Models (MLEM) to predict the daily and monthly price of the Sugar No. 14 contract in the New York Board of Trade. This technique can be seen as a forecasting method that performs data exploratory analysis and mathematical modeling simultaneously. Given a set of data points, the basic idea is as follows: 1) a Kohonen Neural Network is used to divide the data into clusters of points, 2) several modeling techniques are then used to construct competing models for each cluster, 3) the best model for each cluster is then selected and called the Local Expert Model. Finally, a so-called Gating Network combines the outputs of all Local Expert Models. For comparison purposes, the same modeling techniques are also evaluated when acting as Global Experts, i. e., when the technique uses the entire data set without any clustering.

Palavras-chave : mixture of local expert models; forecasting time series; neural networks.

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