Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface.

ABSTRACT: This study investigated the importance of applying explainable artificial intelligence (XAI) on different machine learning (ML) models developed to predict the strength characteristics of basalt-fiber reinforced concrete (BFRC). Even though ML is widely adopted in strength prediction in concrete, the black-box nature of predictions hinders the interpretation of results. Among several attempts to overcome this limitation by using explainable AI, researchers have employed only a single explanation method. In this study, we used three tree-based ML models (Decision tree, Gradient Boosting tree, and Light Gradient Boosting Machine) to predict the mechanical strength characteristics (compressive strength, flexural strength, and tensile strength) of basal fiber reinforced concrete (BFRC). For th

SUBMITTER: Kulasooriya WKVJB 

PROVIDER: S-EPMC10423212 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature