YAPAY SİNİR AĞI İLE GÜÇLENDİRİLMİŞ GENETİK ALGORİTMA VE TERSTEN KANAT PROFİLİ DİZAYNI

In this study, an augmented genetic algorithm via artificial neural network has been introduced, and its implementation to the inverse airfoil design problem is demonstrated. Neural network and a real coded genetic algorithm are hybridized in a new way with the purpose of getting a faster algorithm. In this approximation, instead of predicting computational fluid dynamics calculations of a candidate airfoil, neural network is used for predicting candidate itself. This powerful method is tested for an inverse airfoil design problem in transonic flow cases. The computational efficiency of this implemented algorithm is tremendously high, and due to still being genetic algorithm based technique, this new method is also as robust as the pure genetic algorithms