Structural parameters optimization of submerged inlet using least squares support vector machines and improved genetic algorithm-particle swarm optimization approach

Structural parameters optimization of submerged inlet using least squares support vector machines and improved genetic algorithm-particle swarm optimization approach

It is important to optimize the structure of inlet due to the increasing demand of ram air. In this paper, structural optimization of the submerged inlet is pursued using a hybrid model by integrating least squares support vector machines (LS-SVM) prediction model and improved genetic algorithm-part...

Full description

Bibliographic Details
Main Authors: Houju Pei, Yonglong Cui, Benben Kong, Yanlong Jiang, Hong Shi
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
aircraft submerged inlet
structural parameters optimization
ls-svm prediction model
ga-pso
cfd
artificial intelligence methods
Online Access:http://dx.doi.org/10.1080/19942060.2021.1893226

Internet

http://dx.doi.org/10.1080/19942060.2021.1893226

Similar Items