Improving weighted information criterion by using optimization
Küçük Resim Yok
Tarih
2010
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER SCIENCE BV
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Although artificial neural networks (ANN) have been widely used in forecasting time series, the determination of the best model is still a problem that has been studied a lot. Various approaches available in the literature have been proposed in order to select the best model for forecasting in ANN in recent years. One of these approaches is to use a model selection strategy based on the weighted information criterion (WIC). WIC is calculated by summing weighted different selection criteria which measure the forecasting accuracy of an ANN model in different ways. In the calculation of WIC, the weights of different selection criteria are determined heuristically. In this study, these weights are calculated by using optimization in order to obtain a more consistent criterion. Four real time series are analyzed in order to show the efficiency of the improved WIC. When the weights are determined based on the optimization, it is obviously seen that the improved WIC produces better results. (C) 2009 Elsevier B.V. All rights reserved.
Açıklama
Anahtar Kelimeler
Artificial neural networks, Consistency, Forecasting, Model selection, Time series, Weighted information criterion
Kaynak
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
WoS Q Değeri
Q2
Scopus Q Değeri
Q2
Cilt
233
Sayı
10
