Comparison between Multiple Regression Analysis, Polynomial Regression Analysis, and an Artificial Neural Network for Tensile Strength Prediction of BFRP and GFRP

Comparison between Multiple Regression Analysis, Polynomial Regression Analysis, and an Artificial Neural Network for Tensile Strength Prediction of BFRP and GFRP

In this study, multiple regression analysis (MRA) and polynomial regression analysis (PRA), which are traditional statistical methods, were applied to analyze factors affecting the tensile strength of basalt and glass fiber-reinforced polymers (FRPs) exposed to alkaline environments and predict the...

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Bibliographic Details
Main Authors: Younghwan Kim, Hongseob Oh
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Materials
Subjects:
GFRP
BFRP
tensile strength prediction
multiple regression analysis
response surface
polynomial regression
Online Access:https://www.mdpi.com/1996-1944/14/17/4861

Internet

https://www.mdpi.com/1996-1944/14/17/4861

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