AbstractA new optimization algorithm called multi-frequency vibrational genetic algorithm (mVGA) is significantly improved and tested for two different test cases: an inverse design of an airfoil in subsonic flow and a direct shape optimization of an airfoil in transonic flow. The algorithm emphasizes a new mutation application strategy and diversity variety, such as, the global random diversity and the local controlled diversity. The local controlled diversity is based on either a fuzzy logic controller or an artificial neural network depending on the problem type. For both of the demonstration problems considered, remarkable reductions in the computational times have been accomplished.
Vibrational genetic algorithm enhanced with fuzzy logic and neural networks
Aerospace Science and Technology ; 14 , 1 ; 56-64
2009-11-04
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Vibrational genetic algorithm enhanced with fuzzy logic and neural networks
Online Contents | 2010
Vibrational genetic algorithm enhanced with neural networks in RCS problems
Emerald Group Publishing | 2011
|Vibrational genetic algorithm enhanced with neural networks in RCS problems
Online Contents | 2011
|Fuzzy Logic, Neural Networks, and Soft Computing
British Library Conference Proceedings | 1993
|