A simple and efficient approach to train artificial neural networks using a genetic algorithm to calculate the resonant frequency of an RMA on thick substrate | Zendy

Khuntia Bonomali | Zendy; Pattnaik Shyam S. | Zendy; Panda Dhruba C. | Zendy; Neog Dipak K. | Zendy; Devi S. | Zendy; Dutta Malay | Zendy

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A simple and efficient approach to train artificial neural networks using a genetic algorithm to calculate the resonant frequency of an RMA on thick substrate

Author(s) -

Khuntia Bonomali,

Pattnaik Shyam S.,

Panda Dhruba C.,

Neog Dipak K.,

Devi S.,

Dutta Malay

Publication year - 2004

Publication title -

microwave and optical technology letters

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.304

H-Index - 76

eISSN - 1098-2760

pISSN - 0895-2477

DOI - 10.1002/mop.20126

Subject(s) - artificial neural network , genetic algorithm , simple (philosophy) , backpropagation , microwave , antenna (radio) , electromagnetics , field (mathematics) , microstrip , algorithm , electronic engineering , computer science , engineering , artificial intelligence , electrical engineering , machine learning , telecommunications , mathematics , philosophy , epistemology , pure mathematics

Both genetic algorithms (GAs) and artificial neural networks (ANNs) have been used in the field of computational electromagnetics as the most powerful optimizing tools. In this paper, a simple and efficient method is presented to handle the problem of competing convention while training an ANN by using a GA. This technique is applied to calculate the resonant frequency of a thick‐substrate rectangular microstrip antenna (RMA). The training time is less than that of a normal feed‐forward backpropagation algorithm. The measured results are in very good agreement with experimental results. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 41: 313–315, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20126

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