Generalized regression.
Published in Chapter:
Modeling Antenna Radiation Using Artificial Intelligence Techniques: The Case of a Circular Loop Antenna
Theodoros N. Kapetanakis (Department of Electronic Engineering, Hellenic Mediterranean University, Greece), Ioannis O. Vardiambasis (Department of Electronic Engineering, Hellenic Mediterranean University, Greece), Melina P. Ioannidou (Department of Information and Electronic Engineering, International Hellenic University, Greece), and Antonios I. Konstantaras (Department of Electronic Engineering, Hellenic Mediterranean University, Greece)
Copyright: © 2021
|Pages: 40
DOI: 10.4018/978-1-7998-4879-0.ch007
Abstract
The forward and the inverse problem of a thin, circular, loop antenna that radiates in free space is modeled and solved by using soft computing techniques such as artificial neural networks and adaptive neuro fuzzy inference systems. On the one hand, the loop radius and the observation angle serve as inputs to the forward model, whereas the radiation intensity is the output. On the other hand, the electric field intensity and the loop radius are the input and output, respectively, to the inverse model. Extensive numerical tests indicate that the results predicted by the proposed models are in excellent agreement with theoretical data obtained from the existing analytical solutions of the forward problem. Thus, the employment of artificial intelligence techniques for tackling electromagnetic problems turns out to be promising, especially regarding the inverse problems that lack solution with other methods.