Predicting the compressive strength of polymer-infused bricks: A machine learning approach with SHAP interpretability - Chandra, Sathvik Sharath; Kumar, Rakesh; Arjunasamy, Archudha; Galagali, Sakshi; Tantri, Adithya; Naganna, Sujay Raghavendra (Scientific reports, 2025)
Keywords: 639/301/1023; 639/705/794; Accuracy; AdaBoost; Aquatic life; Aquatic organisms; Artificial neural network; Cement; Fly ash; Humanities and Social Sciences; Learning algorithms; Machine learning; Mix proportion; multidisciplinary; Neural networks; Polymer brick; Polymers; Polypropylene; Prediction models; Sand; Science; Science (multidisciplinary); Support vector machine; Sustainable materials; Waste materials; Waste materials; AdaBoost; Mix proportion; Random forest; Artificial neural network; Support vector machine; Polymer brick