Epilepsy Diagnosis Using Artificial Neural Network Learned by PSO -- 2
Küçük Resim Yok
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
TURGUT OZAL UNIV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, epilepsy diagnosis has been investigated by using Electroencephalogram (EEG) records. For this purpose, a technique as the classifier Artificial Neural Networks (ANN), which is frequently used and known as an active classification technique, is used. Particle Swarm Optimization (PSO) method is preferred as training algorithm for ANN. PSO based neural network model (PSONN) is diversified according to PSO variants and seven PSO based neural network models are described. In these models, PSONN3 and PSONN4 are determined as appropriate models for the classification. In addition, different number of neurons, iterations/generations and swarm sizes have been considered and tried. Obtained results of the models have been evaluated.
Açıklama
9th International Conference on Electronics Computer and Computation (ICECCO 2012) -- NOV 01-03, 2012 -- Ankara, TURKEY
Anahtar Kelimeler
Artificial neural networks, EEG, epilepsy diagnosis, inertia weight, particle swarm optimization
Kaynak
ICECCO'12: 9TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTER AND COMPUTATION
WoS Q Değeri
N/A
