Utilization of metaheuristic-based regression analysis to calculate the modified high-performance concrete's compressive strength

Liming  Mu

doi:10.6180/jase.202508_28(8).0012

Utilization of metaheuristic-based regression analysis to calculate the modified high-performance concrete's compressive strength

Civil Engineering

Liming MuThis email address is being protected from spambots. You need JavaScript enabled to view it.

Department of Architectural Engineering, Shijiazhuang College of Applied Technology, Shijiazhuang 050000, China

Received: February 18, 2024
Accepted: September 12, 2024
Publication Date: November 16, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202508_28(8).0012

Different regression analytics were used to provide a unique approach to testing the compressive strength (CS) of high-performance concrete (HPC) made with blast furnace slag and fly ash. In this study, it was employed the equilibrium optimizer (EO) and the arithmetic optimization algorithm (AOA) to identify key regression method variables (i.e., Support vector regression (SVR)) which could be adjusted to improve performance. The suggested approaches were created utilizing 1030 tests, eight inputs (aggregates, primary mix designs, admixtures, and curing age), and the CS as the forecasting objective. The results were then compared to those in the corpus of already published scientific literature. Estimation outcomes point to the potential benefit of combining EO-SVR with AOA-SVR analysis. The AOA-SVR displayed significantly better R2 (0.9874 and 0.993) and lower RMSEvalues as compared to the EO-SVR. Comparing the data demonstrates how much better the created AOA-SVR is than anything that has previously been reported. Overall, the suggested technique for determining the CS of HPC augmented with fly ash and blast furnace slag may be used using the AOA-SVR analysis.

Keywords: Compressive Strength; Blast Furnace Slag; High-Performance Concrete; Support Vector Regression; Fly Ash; Artificial Intelligence

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