A new architecture selection strategy in solving seasonal autoregressive time series by artificial neural networks

Aladag, Cagdas Hakan and Egrioglu, Erol and Gunay, Suleyman (2008) A new architecture selection strategy in solving seasonal autoregressive time series by artificial neural networks. Hacettepe Journal of Mathematics and Statistics, 37 (2). pp. 185-200. ISSN 1303-5010

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Abstract

The only suggestions given in the literature for determining the archi- tecture of neural networks are based on observations, and a simulation study to determine the architecture has not yet been reported. Based on the results of the simulation study described in this paper, a new architecture selection strategy is proposed and shown to work well. It is noted that although in some studies the period of a seasonal time series has been taken as the number of inputs of the neural network model, it is found in this study that the period of a seasonal time series is not a parameter in determining the number of inputs.

Item Type:
Journal Article
Journal or Publication Title:
Hacettepe Journal of Mathematics and Statistics
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2608
Subjects:
ID Code:
139570
Deposited By:
Deposited On:
13 Dec 2019 15:20
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 12:22