Yayın: Hybrid neural network and genetic algorithm based machining feature recognition
Tarih
Kurum Yazarları
Öztürk, Nursel
Öztürk, Ferruh
Yazarlar
Danışman
Dil
Türü
Yayıncı:
Springer
Dergi Başlığı
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Özet
In this research, neural networks (NNs) and genetic algorithms (GAs) are used together in a hybrid approach to reduce the computational complexity of feature recognition problem. The proposed approach combines the characteristics of evolutionary technique and NN to overcome the shortcomings of feature recognition problem. Consideration is given to reduce the computational complexity of network with specific interest to design the optimum network architecture using GA input selection approach. In order to evaluate the performance of the proposed system, experimental results are compared with previous NN based feature recognition research.
Açıklama
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Anahtar Kelimeler:
Konusu
Computer science, Engineering, Feature recognition, Neural networks, Genetic input selection, Manufacturing features, Design, Classification, System, Search, Model, Backpropagation, Computational complexity, Computer aided manufacturing, Feature extraction, Genetic algorithms, Image processing, Machining, Mathematical models, Parameter estimation, Problem solving, Computer aided production systems, Feature recognition, Genetic input selection, Network model, Neural networks
Alıntı
Öztürk, N. ve Öztürk, F. (2004). “Hybrid neural network and genetic algorithm based machining feature recognition”. Journal of Intelligent Manufacturing, 15(3), 287-298.