Prediction of the Compressive Strength of Fly Ash Geopolymer Concrete by an Optimised Neural Network Model

Prediction of the Compressive Strength of Fly Ash Geopolymer Concrete by an Optimised Neural Network Model

This article presents a regression tool for predicting the compressive strength of fly ash (FA) geopolymer concrete based on a process of optimising the Matlab code of a feedforward layered neural network (FLNN). From the literature, 189 samples of different FA geopolymer concrete mix-designs were c...

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Bibliographic Details
Main Authors: Ali Abdulhasan Khalaf, Katalin Kopecskó, Ildiko Merta
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Polymers
Subjects:
fly ash
geopolymer concrete
alkali-activated binder
compressive strength
feedforward layered neural network
Matlab code
Online Access:https://www.mdpi.com/2073-4360/14/7/1423

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