A Proposed Soft Computing Model for Ultimate Strength Estimation of FRP-Confined Concrete Cylinders

A Proposed Soft Computing Model for Ultimate Strength Estimation of FRP-Confined Concrete Cylinders

In this paper, the feed-forward backpropagation neural network (FFBPNN) is used to propose a new formulation for predicting the compressive strength of fiber-reinforced polymer (FRP)-confined concrete cylinders. A set of experimental data has been considered in the analysis. The data include informa...

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Bibliographic Details
Main Authors: Reza Kamgar, Hosein Naderpour, Houman Ebrahimpour Komeleh, Anna Jakubczyk-Gałczyńska, Robert Jankowski
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Applied Sciences
Subjects:
frp
soft computing
compressive strength
confined concrete
artificial neural network
Online Access:https://www.mdpi.com/2076-3417/10/5/1769

Internet

https://www.mdpi.com/2076-3417/10/5/1769

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