Machine learning model to predict slump, VEBE and compaction factor of M-Sand and shredded PET bottles concrete

Nadimalla, Altamashuddinkhan and Masjuki, Siti Aliyyah and Saad, Siti Asmahani and Ali, Maisarah (2021) Machine learning model to predict slump, VEBE and compaction factor of M-Sand and shredded PET bottles concrete. In: 5th International Conference on Mechanical, Automotive and Aerospace Engineering 2021 (ICMAAE'21), 22 - 23 June 2021, Virtual.

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Abstract

This paper aims to develop the machine learning model with the help of experimental data such as slump, VEBE and compaction factor of concrete incorporated with shredded Polyethylene Terephthalate (PET) bottles, Manufactured Sand (M-sand) and River sand as find aggregates replacement in concrete mixtures. The machine learning model is developed by using different machine learning techniques such as multiple regression and decision tree.

Item Type:	Proceeding Paper (Slide Presentation)
Uncontrolled Keywords:	Slump, VEBE, Compaction Factor, Machine Learning
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA401 Materials of engineering and construction
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Civil Engineering
Depositing User:	Ts. Dr Siti Aliyyah Masjuki
Date Deposited:	14 Feb 2025 16:32
Last Modified:	14 Feb 2025 16:32
URI:	http://irep.iium.edu.my/id/eprint/94482

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