An Efficient Method for Antenna Design Optimization Based on Evolutionary Computation and Machine Learning Techniques

In recent years, various methods from the evolutionary computation (EC) field have been applied to electromagnetic (EM) design problems and have shown promising results. However, due to the high computational cost of the EM simulations, the efficiency of directly using evolutionary algorithms is oft...

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Bibliographic Details
Published in:	IEEE transactions on antennas and propagation Vol. 62; no. 1; pp. 7 - 18
Main Authors:	Bo Liu, Aliakbarian, Hadi, Zhongkun Ma, Vandenbosch, Guy A. E., Gielen, Georges, Excell, Peter
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.01.2014 Institute of Electrical and Electronics Engineers
Subjects:	Antenna design optimization antenna synthesis Antennas Applied classical electromagnetism Applied sciences Computational modeling differential evolution efficient global optimization Electromagnetic wave propagation, radiowave propagation Electromagnetism; electron and ion optics Exact sciences and technology expensive black-box optimization Fundamental areas of phenomenology (including applications) Gaussian process Mathematical model Optimization Physics Predictive models Radiocommunications surrogate model assisted evolutionary algorithm Telecommunications Telecommunications and information theory Training data Performance evaluation Electromagnetism Evolutionary algorithm Industrial application Evolutionary computation Global optimum Antenna design optimization Computational complexity Particle swarm optimization efficient global optimization differential evolution Gaussian process Biomimetics Simulation surrogate model assisted evolutionary algorithm On line processing Artificial intelligence expensive black-box optimization Antenna Antenna synthesis
ISSN:	0018-926X, 1558-2221
Online Access:	Get full text
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