The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON MATHEMATICS
Transactions ID Number: 29-700
Full Name: Dursun Aydýn
Position: Assistant Professor
Age: ON
Sex: Male
Address: Department of statistics muðla university 4800 kötekli Muðla
Country: TURKEY
Tel: +905394968575
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Fax:
E-mail address: duaydin@anadolu.edu.tr
Other E-mails: duaydin@mu.edu.tr
Title of the Paper: A Comparative Study of hybrid, neural networks and nonparametric regression models in time series prediction
Authors as they appear in the Paper: Dursun Aydýn, Mammadagha Mammadov
Email addresses of all the authors: duaydin@mu.edu.tr, mmammadov@anadolu.edu.tr
Number of paper pages: 11
Abstract: This paper presents a comparative study of the hybrid models, neural networks and nonparametric regression models in time series forecasting. The components of these hybrid models are consisting of the nonparametric regression and artificial neural networks models. Smoothing spline, regression spline and additive regression models are considered as the nonparametric regression components. Furthermore, various multilayer perceptron algorithms and radial basis function network model are regarded as the artificial neural networks components. The performances of these models are compared by forecasting the series of number of produced Cars and Domestic product per capita (GDP) data occurred in Turkey. This comparisons show that hybrid models proposed in this paper have denoted much more excellent performance than the hybrid models in literature.
Keywords: Time series, Neural networks, Multilayer perceptrons, Radial basis function, Nonparametric regression, Additive regression model, Hybrid models
EXTENSION of the file: .pdf
Special (Invited) Session: Hybrid Models Combining Neural Networks and Nonparametric Regression Models Used for Time Series Prediction
Organizer of the Session: 618-443
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IP ADDRESS: 88.243.130.221
