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Application of Ensemble Machine Learning Methods to Estimate the Compressive Strength of Fiber-Reinforced Nano-Silica Modified Concrete.
Anjum M, Khan K, Ahmad W, Ahmad A, Amin MN, Nafees A. Anjum M, et al. Polymers (Basel). 2022 Sep 19;14(18):3906. doi: 10.3390/polym14183906. Polymers (Basel). 2022. PMID: 36146051 Free PMC article.
In this study, compressive strength (CS) of fiber-reinforced nano-silica concrete (FRNSC) was anticipated using ensemble machine learning (ML) approaches. Four types of ensemble ML methods were employed, including gradient boosting, random forest, bagging regressor, and Ad …
In this study, compressive strength (CS) of fiber-reinforced nano-silica concrete (FRNSC) was anticipated using ensemble machine lear …
New SHapley Additive ExPlanations (SHAP) Approach to Evaluate the Raw Materials Interactions of Steel-Fiber-Reinforced Concrete.
Anjum M, Khan K, Ahmad W, Ahmad A, Amin MN, Nafees A. Anjum M, et al. Materials (Basel). 2022 Sep 9;15(18):6261. doi: 10.3390/ma15186261. Materials (Basel). 2022. PMID: 36143573 Free PMC article.
Recently, artificial intelligence (AI) approaches have gained the attention of researchers in the civil engineering field for estimating the mechanical characteristics of concrete to save the effort, time, and cost of researchers. Consequently, the current resear …
Recently, artificial intelligence (AI) approaches have gained the attention of researchers in the civil engineering field for estimat …