Initializing artificial neural networks by genetic algorithm to calculate the resonant frequency of single shorting post rectangular patch antenna

2004 ◽  
Author(s):  
S. Devi ◽  
D.C. Panda ◽  
S.S. Pattnaik ◽  
B. Khuntia ◽  
D.K. Neog
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Resonant Frequency ◽  
Patch Antenna ◽  
Rectangular Patch ◽  
Artificial Neural

scholarly journals Comparison of the Resonant Frequency Determination of a Microstrip Patch Antenna using ANN and Analytical Methods

2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Lahcen Aguni ◽  
Samira Chabaa ◽  
Saida Ibnyaich ◽  
Abdelouhab Zeroual
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Dielectric Permittivity ◽  
Resonant Frequency ◽  
Analytical Methods ◽  
Patch Antenna ◽  
Good Argument ◽  
Microstrip Patch ◽  
Rectangular Patch ◽  
Artificial Neural

In this paper we are interested to calculate the resonant frequency of rectangular patch antenna using artificial neural networks based on the multilayered perceptrons. The artificial neural networks built, transforms the inputs which are, the width of the patch W, the length of the patch L, the thickness of the substrate h and the dielectric permittivity to the resonant frequency fr which is an important parameter to design a microstrip patch antenna.The proposed method based on artificial neural networks is compared to some analytical methods using some statistical criteria. The obtained results demonstrate that artificial neural networks are more adequate to achieve the purpose than the other methods and present a good argument with the experimental results available in the literature. Hence, the artificial neural networks can be used by researchers to predict the resonant frequency of a rectangular patch antenna knowing length (L), width (W), thickness (h) and dielectric permittivity with a good accuracy.

MATHEMATICAL SUPPORT FOR INDUCTION SOLDERING CONTROL BASED ON INTELLIGENT METHODS OF INFORMATION PROCESSING

2021 ◽  
pp. 81-87
Author(s):  
А.В. Милов
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Information Processing ◽  
Mathematical Models ◽  
Technological Process ◽  
Artificial Neural ◽  
Intelligent Methods

В статье представлены математические модели на основе искусственных нейронных сетей, используемые для управления индукционной пайкой. Обучение искусственных нейронных сетей производилось с использованием многокритериального генетического алгоритма FFGA. This article presents mathematical models based on artificial neural networks used to control induction soldering. The artificial neural networks were trained using the FFGA multicriteria genetic algorithm. The developed models allow to control induction soldering under conditions of incomplete or unreliable information, as well as under conditions of complete absence of information about the technological process.

Sign in / Sign up

Export Citation Format

Share Document