Comparison of Artificial Neural Network (ANN) and Response Surface Methodology (RSM) in Predicting the Compressive Strength of POFA Concrete

Comparison of Artificial Neural Network (ANN) and Response Surface Methodology (RSM) in Predicting the Compressive Strength of POFA Concrete

This study presents a comparative study between Artificial Neural Network (ANN) and Response Surface Methodology (RSM) in predicting the compressive strength of palm oil fuel ash (POFA) concrete. The comparison was made based on the same experimental datasets. The inputs investigated in this study w...

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Bibliographic Details
Main Authors: Ahmad Nurfaidhi Rizalman, Chen, Choon Lee
Format: Article
Language:English
English
Published: 2020
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:https://eprints.ums.edu.my/id/eprint/26081/1/Comparison%20of%20Artificial%20Neural%20Network%20%28ANN%29%20and%20Response%20Surface%20Methodology%20%28RSM%29%20in%20Predicting%20the%20Compressive%20Strength%20of%20POFA%20Concrete.pdf
https://eprints.ums.edu.my/id/eprint/26081/2/Comparison%20of%20Artificial%20Neural%20Network%20%28ANN%29%20and%20Response%20Surface%20Methodology%20%28RSM%29%20in%20Predicting%20the%20Compressive%20Strength%20of%20POFA%20Concrete1.pdf

Internet

https://eprints.ums.edu.my/id/eprint/26081/1/Comparison%20of%20Artificial%20Neural%20Network%20%28ANN%29%20and%20Response%20Surface%20Methodology%20%28RSM%29%20in%20Predicting%20the%20Compressive%20Strength%20of%20POFA%20Concrete.pdf
https://eprints.ums.edu.my/id/eprint/26081/2/Comparison%20of%20Artificial%20Neural%20Network%20%28ANN%29%20and%20Response%20Surface%20Methodology%20%28RSM%29%20in%20Predicting%20the%20Compressive%20Strength%20of%20POFA%20Concrete1.pdf

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