Extracting the dielectric constant of materials using ABC-based ANNs and NRW algorithms
Yazarlar (5)
Karabük Üniversitesi, Türkiye
University Of Tripoli, Türkiye
Prof. Dr. Muharrem DÜĞENCİ
Karabük Üniversitesi, Türkiye
Tubıtak Marmara Research Center, Türkiye
Karabük Üniversitesi, Türkiye
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Journal of Electromagnetic Waves and Applications |
| Dergi ISSN | 0920-5071 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Makale Dili | İngilizce |
| Basım Tarihi | 08-2016 |
| Cilt No | 30 |
| Sayı | 13 |
| Sayfalar | 1785 / 1799 |
| DOI Numarası | 10.1080/09205071.2016.1215266 |
| Makale Linki | https://www.tandfonline.com/doi/full/10.1080/09205071.2016.1215266 |
| Özet |
| Five different Nicolson–Ross–Weir (NRW) extracting techniques are used to extract the dielectric constants of Teflon, Rexolite, Glass (borosilicate and soda-lime), Paper, and Ultralam 3850HT from S-parameters. The results of these extraction techniques are used to train the Artificial Neural Networks. In order to improve the accuracy of the results, the weights of ANNs are calculated using artificial bee colony estimation method. The results are compared with that obtained using NRW, Newton–Raphson, and genetic algorithm. The obtained results indicate that the proposed model gives good extracted parameters as compared with the previously published results. |
| Anahtar Kelimeler |
| Free space measurement | artificial bee colony | dielectric constant | NRW technique | Newton-Raphson method |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| SCOPUS | 14 |
| Google Scholar | 16 |