Li Heling and Qian YaoThis email address is being protected from spambots. You need JavaScript enabled to view it.
College of Accountancy, Anhui Business and Technology College, Hefei, 231131, Anhui, China
Received: July 1, 2025 Accepted: August 31, 2025 Publication Date: October 19, 2025
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.
Environmental and economic concerns have encouraged civil engineers to explore the integration of recycled materials in novel building operations. Stone matrix asphalt (SMA) is manufactured by amalgamating Trinidad Lake Asphalt (TLA) binder with meticulously quantified proportions of recycled concrete aggregates and natural aggregates (limestone and dust filler). This procedure yields gap-graded SMA. The semi-circular bending test (SCB) criteria were utilized to select the dataset parameters. The Decision Tree Regression (DTR) was used for estimating fracture resistance ( Gf ). The dependability is considerably influenced by the DTR hyperparameters, which must be selected by metaheuristic optimization methods. The Walrus algorithm (WaA) and Northern goshawk algorithm (NGA) are used for this purpose. It is likely that both DTR (WaA) and DTR(NGA) will compute the Gf correctly based on the information supplied. With R2 of 0.9519 and 0.9507, the DTR (NGA) showed notable functional dependability throughout the learning and evaluation. The DTR (WaA) produced values of 0.9818 and 0.9893 that were quite close.
Keywords: Stone matrix asphalt; Recycled concrete; Semi-circular bending test; Estimation; Fracture energy
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