Analysis of C-shaped compact microstrip antennas using deep neural networks optimized by Manta Ray foraging optimization with Lévy-Flight Mechanism

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dc.contributor.authorBiçer, Mustafa Berkan
dc.date.accessioned2023-03-22T19:48:06Z
dc.date.available2023-03-22T19:48:06Z
dc.date.issued2021
dc.departmentBelirleneceken_US
dc.description.abstractIn recent years, microstrip antennas have become a popular research subject with the increasing use of mobile technologies. With the development of neural networks, the design and analysis of microstrip antennas are carried out quickly with high accuracy. However, optimizing the weight matrices and bias vectors of deep neural learning models is an important challenge for engineering problems. This study presents a deep neural network-based (DNN-based) neural model to estimate the gain and scattering parameter (S11) of C-shaped compact microstrip antennas (CCMAs). For this purpose, the S11 and gain values of 324 CCMAs with different physical and electrical properties were obtained using full-wave electromagnetic simulation software based on the finite integration technique (FIT). The data related to 324 CCMAs were used for the training and testing process. The improved manta ray foraging optimization (MRFO) algorithm based on the Lévy-flight (LF) mechanism was used to optimize the connection weights matrices and bias vectors. The MRFO-optimized model has estimation success for training and testing data as 0.925 and 0.922, in terms of R2 score, respectively. The estimated resonant frequencies using the trained model are compared with the studies in the literature, and an average percentage error (APE) of 0.933% is obtained.en_US
dc.identifier.doi10.35377/saucis.04.02.903208
dc.identifier.endpage180en_US
dc.identifier.issn2636-8129
dc.identifier.issue2en_US
dc.identifier.startpage166en_US
dc.identifier.trdizinid502435en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14034/981
dc.identifier.urihttps://doi.org/10.35377/saucis.04.02.903208
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/502435
dc.identifier.volume4en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.journalSakarya University Journal of Computer and Information Sciences (Online)en_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectC-shaped microstrip antennaen_US
dc.subjectS-parameter estimationen_US
dc.subjectgain estimationen_US
dc.subjectdeep neural networksen_US
dc.subjectlévy flight techniqueen_US
dc.subjectmanta ray foraging optimizationen_US
dc.titleAnalysis of C-shaped compact microstrip antennas using deep neural networks optimized by Manta Ray foraging optimization with Lévy-Flight Mechanismen_US
dc.typeArticleen_US

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