천음속 영역의 조파항력 감소를 위한 효율적인 전역적 최적화 기법 연구
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The use of evolutionary algorithm is limited in the field of aerodynamics, mainly because the population-based search algorithm requires excessive CPU time. In this paper a coupling method with adaptive range genetic algorithm for floating point and back-propagation neural network is proposed to efficiently obtain a converged solution. As a result, it is shown that a reduction of 14% and 33% respectively in wave drag and its consumed time can be achieved by the new method.
[1] Akira Oyama,et al. Real-coded adaptive range genetic algorithm applied to transonic wing optimization , 2000, Appl. Soft Comput..
[2] Kyriakos C. Giannakoglou,et al. Design of optimal aerodynamic shapes using stochastic optimization methods and computational intelligence , 2002 .
[3] A. Jahangirian,et al. Airfoil shape parameterization for optimum Navier–Stokes design with genetic algorithm , 2007 .