Abstract
In this study, the boundary coefficients of Transverse Electric (TE) and Transverse Magnetic (TM) modes at a planar slab optic guides are modeled by Neural Networks (NN). After modal analysis, train and test files are prepared for NN. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are performed and compared with each other. NNs are expected to be capable of modeling optical fiber technology in industry based on the same approaches as a result of this study.
Keywords
Computer science
Boundary (topology)
Artificial intelligence
Computer vision
Human–computer interaction
Mathematics
Mathematical analysis
Subject Areas
Advanced Fiber Optic Sensors
·Electrical and Electronic Engineering ·Physical Sciences
Semiconductor Lasers and Optical Devices
·Electrical and Electronic Engineering ·Physical Sciences
Optical Network Technologies
·Electrical and Electronic Engineering ·Physical Sciences
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Industry, innovation and infrastructure 63%
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