Placement score estimation of secondary education transition system (SETS) using artificial neural networks
Küçük Resim Yok
Tarih
2012
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study offers an approach based on artificial neural networks for predicting the placement score of secondary education transition system (SETS). Artificial neural networks have recently become a very important method in the classification and prediction of the problems. Therefore, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) which are among the most preferred artificial neural network architectures were used in this study. Created expert system was trained and tested on a database including 25000 randomly selected records of primary education 8th grade students. Results of this training and testing are comparatively presented within the study. © Sila Science.
Açıklama
Anahtar Kelimeler
Artificial Neural Networks, Multilayer Perceptron, Radial Basis Function, SETS
Kaynak
Energy Education Science and Technology Part A: Energy Science and Research
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
30
Sayı
SPEC .ISS.1
