An Easy Approach for the Selection of Optimal Neural Network Structure (In English)

Year 2009, Volume: 34 Issue: 2, 73 - 81, 01.04.2009

Kıvanç Kılıç Deniz Baş İsmail Hakkı Boyacı

Abstract

Investigation of an optimal topology and parameters of a high performing neural network is a labourintensive process. In this study, the possibility of obtaining the optimal network structure using a script was investigated. For this purpose, making use of a script coded in MATLAB®, all possible networks in the range of investigated network parameters were created and trained. In addition, the networks created with the help of the script were tested and the selected performance parameters (Absolute Average Deviation, Mean Squared Error, and Coefficient of Determination) were calculated. e network model studied was chosen as multilayer perceptron with a feed-forward back propagation algorithm. e investigated parameters of the selected network were number of neurons, training functions, and transfer functions. Additionally, the script was tested on three different data sets. e results indicate that the script can be successfully applied for identification of the network topology and the parameters to be used for the evaluation of the data obtained from kinetic researches.

Keywords

Artificial neural networks, kinetic application, optimization, modeling  

Optimum Yapay Sınır Ağı Yapısının Belirlenmesinde Kolay bir Yaklaşım (İngilizce)

Abstract

Yüksek performansa sahip sinir agının optimum topolojisinin ve parametrelerinin belirlenmesi emek-yogun bir islemdir. Bu çalısma kapsamında, optimum ag yapısının bir kod yardımıyla belirlenmesi incelenmistir. Bu dogrultuda, MATLAB® ile olusturulan kod kullanılarak incelenen parametre aralıgındaki sinir aglarının olusturulması ve egitimi gerçeklestirilmistir. Ayrıca, kullanılan kod yardımıyla elde edilen aglar test edilmekte ve seçilen performans parametrelerinin (Mutlak Ortalama Sapma, Ortalama Karesel Hata ve Determinasyon Katsayısı) hesaplanmaktadır. Çalısma kapsamında, geri yayılımlı ileri beslemeli çok katmanlı sinir agı yapısı model olarak seçilmistir. Seçilen ag yapısı için incelenen parametreler; sinir hücresi sayısı, egitim fonksiyonu ve transfer fonksiyonu olarak belirlenmistir. Bunlara ek olarak, olusturulan kod üç farklı veri seti kullanılarak test edilmistir. Elde edilen sonuçlar, olusturulan kodun kinetik çalısmalar sonucunda elde edilen verilerin incelenmesinde kullanılacak ag topolojisi ve parametrelerinin belirlenmesinde basarılı bir sekilde uygulanacagını göstermektedir.

Keywords

Yapay sinir agları, kinetik uygulama, optimizasyon, modelleme

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