Title
Multilayer Perceptron Models for Band Diagram Prediction in bi-dimensional Photonic Crystals
Date Issued
11 January 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
Universidad Estatal de Campinas
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
We modeled Multilayer Perceptron (MLP) Artificial Neural Network for predicting band diagrams (BD) of bi-dimensional photonic crystals. Datasets for MLP training were created by relating geometric and material properties to BDs of triangular-and square-lattice photonic crystals. We demonstrate that fast-Training MLP models are able to estimate accurate BDs and existing photonic band gaps through rapid computations.
Language
English
OCDE Knowledge area
Ingeniería de sistemas y comunicaciones
Ingeniería eléctrica, Ingeniería electrónica
Subjects
Scopus EID
2-s2.0-85061983075
ISBN of the container
9781538667026
Conference
2018 SBFoton International Optics and Photonics Conference, SBFoton IOPC 2018
Sponsor(s)
This work was supported by the Coordenac¸ão de Aperfeic¸oamento de Pessoal de Nível Superior (CAPES), the Conselho Nacional de Desenvolvimento Tecnológico (CNPq) under grant #312110/2016-2, and the Fundac¸ão de Amparo à Pesquisa do Estado de São Paulo (FAPESP) under project no. 2015/24517-8, all from Brazil.
Sources of information:
Directorio de Producción Científica
Scopus