MACHINE LEARNING-BASED MODELING WITH OPTIMIZATION ALGORITHM FOR PREDICTING MECHANICAL PROPERTIES OF SUSTAINABLE CONCRETE

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dc.contributor.authorShah, Muhammad Izhar
dc.contributor.authorMemon, Shazim Ali
dc.contributor.authorNiazi, Muhammad Sohaib Khan
dc.contributor.authorAmin, Muhammad Nasir
dc.contributor.authorAslam, Fahid
dc.contributor.authorJaved, Muhammad Faisal
dc.date.accessioned2021-12-22T08:41:17Z
dc.date.available2021-12-22T08:41:17Z
dc.date.issued2021-03-04
dc.description.abstractIn this research, multiexpression programming (MEP) has been employed to model the compressive strength, splitting tensile strength, and flexural strength of waste sugarcane bagasse ash (SCBA) concrete. Particle swarm optimization (PSO) algorithm was used to fine-tune the hyperparameter of the proposed MEP. The formulation of SCBA concrete was correlated with five input parameters. To train and test the proposed model, a large number of data were collected from the published literature. Afterward, waste SCBA was collected, processed, and characterized for partial replacement of cement in concrete. Concrete specimens with varying proportion of SCBA were prepared in the laboratory, and results were used for model validation. The performance of the developed models was then evaluated by statistical criteria and error assessment tests. The result shows that the performance of MEP with PSO algorithm significantly enhanced its accuracy. The essential input variables affecting the output were revealed, and the parametric analysis confirms that the models are accurate and have captured the essential properties of SCBA. Finally, the cross validation ensured the generalized capacity and robustness of the models. Hence, the adopted approach, i.e., MEP-based modeling with PSO, could be an effective tool for accurate modeling of the concrete properties, thus directly contributing to the construction sector by consuming waste and protecting the environment.en_US
dc.identifier.citationShah, M. I., Memon, S. A., Khan Niazi, M. S., Amin, M. N., Aslam, F., & Javed, M. F. (2021). Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete. Advances in Civil Engineering, 2021, 1–15. https://doi.org/10.1155/2021/6682283en_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/5954
dc.language.isoenen_US
dc.publisherAdvances in Civil Engineeringen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectType of access: Open Accessen_US
dc.subjectmultiexpression programmingen_US
dc.titleMACHINE LEARNING-BASED MODELING WITH OPTIMIZATION ALGORITHM FOR PREDICTING MECHANICAL PROPERTIES OF SUSTAINABLE CONCRETEen_US
dc.typeArticleen_US
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