An ensemble learning-based prediction model for the compressive strength degradation of concrete containing superabsorbent polymers (SAP).

ABSTRACT: Super absorbent polymer (SAP) has a capacity to enhance the characteristics of cementitious composites in both their fresh and hardened forms. However, it is essential to recognize that the strength of SAP concrete may decrease. By altering the concrete composition and selecting the appropriate type of SAP, it is possible to reduce this reduction. This work employs machine learning (ML) to tackle the issue of strength degradation. The analysis considers ten distinct variables linked to concrete composition and the type of SAP. The study uses machine learning approaches that involve both regression and classification tasks. The use of ensemble learning greatly improves the quality and accuracy of the results, showing its superiority in combining several models to produce more precise predic

SUBMITTER: Hosseinzadeh M 

PROVIDER: S-EPMC11315962 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature