Predicting slump, slump flow and compressive strength of concrete using Type-1 TSK Fuzzy System

Aghajari,, Ali, Yadollahi, Samin, Tahayori, Hooman, Bahadori-Jahromi, Ali ORCID logoORCID: https://orcid.org/0000-0003-0405-7146 and Hosseini Moreh, Amir (2026) Predicting slump, slump flow and compressive strength of concrete using Type-1 TSK Fuzzy System. In: 17th International Joint Conference on Computational Intelligence (IJCCI 2025), 22–24 October 2025, Marbella, Spain.

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Abstract

Concrete is one of the most important construction materials in industry due to its versatile applicability in commercial and industrial projects. Slump test measures the workability or consistency of concrete and slump flow test measures flow of self-compacting concrete (SCC). Concrete production with an acceptable slump value and also the related testing procedures are complex and uncertain. In this research, slump, slump flow, and compressive strength of concrete are examined by developing a Type-1 Takagi-Sugeno-Kang (TSK) fuzzy inference system. The proposed inference system is evaluated using root mean squared error (RMSE) and mean absolute error (MAE) metrics. The results obtained from the implemented fuzzy inference system show competitive performance compared to the existing machine learning and neural network models.

Item Type: Conference or Workshop Item (Paper)
ISSN: 1865-0929
ISBN: 9783032156310
Identifier: 10.1007/978-3-032-15632-7_36
Identifier: 10.1007/978-3-032-15632-7_36
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Date Deposited: 05 Feb 2026
URI: https://repository.uwl.ac.uk/id/eprint/14524
Sustainable Development Goals: Goal 9: Industry, Innovation, and Infrastructure Sustainable Development Goals: Goal 11: Sustainable Cities and Communities Sustainable Development Goals: Goal 12: Responsible Consumption and Production Sustainable Development Goals: Goal 13: Climate Action

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