Use of Artificial Neural Networks for Multilayer Waveguide Analysis
Year: 2024
Type: conference-paper
Abstract: " The need to optimize processes has led to the construction of methodscapable of performing tasks with more consistency and accuracy. The present workproposes the optimization of a multilayer waveguide through computational algorithms.Neural Networks were developed with different configurations and trained with differentmethods: Cross Validation and Standard Training. The architecture consists of 7 inputsparameters and one output, with 3 hidden layers. The neural network with the bestperformance presented a Mean Square Error of 1.070×10-11, regression 0.999996 and16.25 seconds of processing, highlighting the Tansig activation function, evaluated asthe best function among those used."
Authors: Arlindo José da Silva Neto, Roney das Mercês Cerqueira, Anderson Dourado Sisnando
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4406753203