A new model selection strategy in artificial neural networks

Eǧrioǧlu, Erol and Aladaǧ, Çaǧdaş Hakan and Günay, Süleyman (2008) A new model selection strategy in artificial neural networks. Applied Mathematics and Computation, 195 (2). pp. 591-597. ISSN 0096-3003

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In recent years, artificial neural networks have been used for time series forecasting. Determining architecture of artificial neural networks is very important problem in the applications. In this study, the problem in which time series are forecasted by feed forward neural networks is examined. Various model selection criteria have been used for the determining architecture. In addition, a new model selection strategy based on well-known model selection criteria is proposed. Proposed strategy is applied to real and simulated time series. Moreover, a new direction accuracy criterion called modified direction accuracy criterion is discussed. The new model selection strategy is more reliable than known model selection criteria.

Item Type:
Journal Article
Journal or Publication Title:
Applied Mathematics and Computation
Uncontrolled Keywords:
?? artificial neural networksfeed forward neural networksmodel selection criteriatime series forecastingcomputational mathematicsapplied mathematics ??
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Deposited On:
13 Dec 2019 15:15
Last Modified:
15 Jul 2024 20:12