Predicting compressive strength of eco-friendly plastic sand paver blocks using gene expression and artificial intelligence programming.
Sci Rep
; 13(1): 12149, 2023 07 27.
Article
en En
| MEDLINE
| ID: mdl-37500697
ABSTRACT
Plastic sand paver blocks provide a sustainable alternative by using plastic waste and reducing the need for cement. This innovative approach leads to a more sustainable construction sector by promoting environmental preservation. No model or Equation has been devised that can predict the compressive strength of these blocks. This study utilized gene expression programming (GEP) and multi-expression programming (MEP) to develop empirical models to forecast the compressive strength of plastic sand paver blocks (PSPB) comprised of plastic, sand, and fibre in an effort to advance the field. The database contains 135 results for compressive strength with seven input parameters. The R2 values of 0.87 for GEP and 0.91 for MEP for compressive strength reveal a relatively significant relationship between predicted and actual values. MEP outperformed GEP by displaying a higher R2 and lower values for statistical evaluations. In addition, a sensitivity analysis was conducted, which revealed that the sand grain size and percentage of fibres play an essential part in compressive strength. It was estimated that they contributed almost 50% of the total. The outcomes of this research have the potential to promote the reuse of PSPB in the building of green environments, hence boosting environmental protection and economic advantage.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
2_ODS3
Problema de salud:
2_quimicos_contaminacion
Asunto principal:
Plásticos
/
Arena
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Sci Rep
Año:
2023
Tipo del documento:
Article
País de afiliación:
Malasia