Academic Journal
A machine-learning-based epistemic modeling framework for textile antenna design
| العنوان: | A machine-learning-based epistemic modeling framework for textile antenna design |
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| المؤلفون: | De Witte, Duygu, Spina, Domenico, De Ridder, Simon, Grassi, Flavia, Rogier, Hendrik, Vande Ginste, Dries |
| المصدر: | IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS ; ISSN: 1536-1225 ; ISSN: 1548-5757 |
| سنة النشر: | 2019 |
| المجموعة: | Ghent University Academic Bibliography |
| مصطلحات موضوعية: | Technology and Engineering, POLYNOMIAL CHAOS, MATHEMATICAL-THEORY, UNCERTAINTY, Bayesian optimization (BO), epistemic uncertainty, fuzzy variables, (FVs), Gaussian process (GP) textile antenna |
| الوصف: | A novel machine-learning-based framework to evaluate the effect of design parameters affected by epistemic uncertainty on the performance of textile antennas is presented in this letter. In particular, epistemic variations are characterized in the framework of possibility theory, which is combined with Bayesian optimization to accurately and efficiently perform uncertainty quantification. A suitable application example validates the proposed method. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | https://biblio.ugent.be/publication/8638548; http://hdl.handle.net/1854/LU-8638548; http://dx.doi.org/10.1109/LAWP.2019.2933306; https://biblio.ugent.be/publication/8638548/file/8638549 |
| DOI: | 10.1109/LAWP.2019.2933306 |
| الاتاحة: | https://biblio.ugent.be/publication/8638548 http://hdl.handle.net/1854/LU-8638548 https://doi.org/10.1109/LAWP.2019.2933306 https://biblio.ugent.be/publication/8638548/file/8638549 |
| Rights: | No license (in copyright) ; info:eu-repo/semantics/restrictedAccess |
| رقم الانضمام: | edsbas.5BB820B8 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1109/LAWP.2019.2933306 |
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