Abstract
An improved particle swarm optimization algorithm is proposed and tested for two different test cases: surface fitting of a wing shape and an inverse design of an airfoil in subsonic flow. The new algorithm emphasizes the use of an indirect design prediction based on a local surrogate modeling in particle swarm optimization algorithm structure. For all the demonstration problems considered herein, remarkable reductions in the computational times have been accomplished. © 2013 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Pehlivanoglu, Y. V. (2013). Improved particle swarm optimization method in inverse design problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7902 LNCS, pp. 218–231). https://doi.org/10.1007/978-3-642-38679-4_21
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