Modelling Flexible Pavement Deterioration with Artificial Neural Networks

1. Introduction

Practitioners have long relied on empirical rules to design smart grids, yet these often neglect the complexity of flexible pavement deterioration. Numerical simulations are complemented by artificial neural networks to cross-check the predicted trends. Sensitivity analysis showed that 3 parameters govern more than 56% of the variability. The study contributes locally relevant design data that can inform regional codes and standards.

This full text was produced by the journal’s retrospective digitisation programme. Section headings follow the printed original.

2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

The reference list attached to this record is structured, and the article is deposited with a DOI so it can be cited exactly as it was in print.