Neural Boundary Conditions in Optic Guides
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2015, Vol 3, Issue 3
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.
Authors and Affiliations
Pınar ÖZKAN BAKBAK| Yildiz Technical University, Department of Electronic and Communication Engineering, Davutpasa, 34220, Istanbul, Turkey
Keywords
Related Articles
- EP ID EP780
- DOI 10.18201/ijisae.04354
- Views 428
- Downloads 23
Power System Contingency Ranking using Fuzzy Logic Based Approach
Voltage stability is a major concern in planning and operations of power systems. It is well known that voltage instability and collapse have led to major system failures. Modern transmission networks are more heavily lo...
Predicting Student Success in Courses via Collaborative Filtering
Based on their skills and interests, students’ success in courses may differ greatly. Predicting student success in courses before they take them may be important. For instance, students may choose elective courses that...
Editorial Team
Validation of Registration for Renal Dynamic Contrast Enhanced MRI Imaging
In Dynamic Contrast Enhanced Resonance Imaging (DCE-MRI), abdomen is scanned repeatedly and rapidly after injection of a contrast agent. During data acquisition, collected images suffer from the motion induced by the pat...
A simple Mathematical Fuzzy Model of Brain Emotional Learning to Predict Kp Geomagnetic Index
In this paper, we propose fuzzy mathematical model of brain limbic system (LS) which is responsible for emotional stimuli. Here the proposed model is utilized to predict the chaotic activity of the earth’s magnetosphere....