مشروع البحث: DEVELOPMENT OF PREDICTIVE MODELS FOR FLEXIBLE PAVEMENT MAINTENANCE IN TROPICAL REGIONS
| dc.contributor.advisor | Assoc. Prof. Dr. Nur Izzi Md Yusoff | |
| dc.date.accessioned | 2026-07-20T07:26:38Z | |
| dc.date.available | 2026-07-20T07:26:38Z | |
| dc.description | Pavement maintance mangement (PMM) depend on performance deterioration models to predict the existing and future condition of pavements, facilitating with effect optimum maintenance which led to extend the service life of specific sections (Tavakol et al. 2025). The performance of flexible pavements is influenced by various factors, including distresses such as linier cracking, rutting, and moisture damage, as well as the material properties and thickness of each pavement layer (Koh et al. 2025). Traffic loads and environmental factors, such as temperature and moisture, also play significant roles in pavement deterioration. Flexible pavements consist of several layers, including the asphalt layer, base layer, subbase layer, and subgrade layer. Moreover, the modulus of elasticity is the most significant material property, as it represents the stiffness of the pavement and its capacity to resist permanent deformation | |
| dc.description.abstract | Information on roadway pavement surface distress is critical to effective pavement asset management. Accordingly, transportation agencies at all levels invest significant time and resources in routinely collecting data on pavement surface distress conditions, which serve as the foundation of their asset management programs. These data enable agencies to make informed decisions about maintenance and rehabilitation. However, current methods for evaluating pavement surface distress are both time-consuming and costly. These challenges can be addressed by leveraging decision-makers' expertise and experience to identify appropriate maintenance solutions. This research focuses on three models namely the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and response surface methodology (RSM). | |
| dc.identifier | 1341 | |
| dc.identifier.uri | https://dspace.academy.edu.ly/handle/123456789/2449 | |
| dc.subject | PREDICTIVE MODELS FOR FLEXIBLE | |
| dc.title | DEVELOPMENT OF PREDICTIVE MODELS FOR FLEXIBLE PAVEMENT MAINTENANCE IN TROPICAL REGIONS | |
| dspace.entity.type | Project | |
| project.endDate | 2025 | |
| project.funder.name | العلوم والهندسة البيئية | |
| project.investigator | عبد الرحمن ابراهيم محمد | |
| project.startDate | 2024 |