Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network

Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network

An artificial neural network (ANN) was constructed and trained for predicting pressure sensitivity using an experimental dataset consisting of luminophore content and paint thickness as chemical and physical inputs. A data augmentation technique was used to increase the number of data points based o...

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Bibliographic Details
Main Authors: Mitsugu Hasegawa, Daiki Kurihara, Yasuhiro Egami, Hirotaka Sakaue, Aleksandar Jemcov
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Sensors
Subjects:
pressure-sensitive paint
artificial neural network
machine learning
data augmentation
Online Access:https://www.mdpi.com/1424-8220/21/15/5188

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https://www.mdpi.com/1424-8220/21/15/5188

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