Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Algorithm for Spatial Clustering of Pavement Segments
Abstract: An algorithm is developed to enable the Georgia Department of Transportation (GDOT) to determine pavement preservation project termini by analyzing segment‐level pavement condition rating. This article formulates a new spatial search model for determining appropriate pavement preservation project termini. A spatial clustering algorithm using fuzzy c‐mean clustering is developed to minimize the rating variation in each cluster (project) of pavement segments while considering minimal project scope (i.e., length) and cost, initial setup cost, and barriers, such as bridges. A case study using the actual roadway and pavement condition data in fiscal year 2005 on Georgia State Route 10 shows that the proposed algorithm can identify more appropriate segment clustering scheme, than the historical project termini. The benefits of using the developed algorithm are summarized, and recommendations for future research are discussed.
Algorithm for Spatial Clustering of Pavement Segments
Abstract: An algorithm is developed to enable the Georgia Department of Transportation (GDOT) to determine pavement preservation project termini by analyzing segment‐level pavement condition rating. This article formulates a new spatial search model for determining appropriate pavement preservation project termini. A spatial clustering algorithm using fuzzy c‐mean clustering is developed to minimize the rating variation in each cluster (project) of pavement segments while considering minimal project scope (i.e., length) and cost, initial setup cost, and barriers, such as bridges. A case study using the actual roadway and pavement condition data in fiscal year 2005 on Georgia State Route 10 shows that the proposed algorithm can identify more appropriate segment clustering scheme, than the historical project termini. The benefits of using the developed algorithm are summarized, and recommendations for future research are discussed.
Algorithm for Spatial Clustering of Pavement Segments
Yang, Chientai (Autor:in) / Tsai, Yichang (James) (Autor:in) / Wang, Zhaohua (Autor:in)
Computer‐Aided Civil and Infrastructure Engineering ; 24 ; 93-108
01.02.2009
16 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Algorithm for Spatial Clustering of Pavement Segments
| Wiley | 2009
Algorithm for Spatial Clustering of Pavement Segments
| Online Contents | 2009
Grouping Pavement Segments to Form Realistic Projects
| British Library Online Contents | 2015