Title |
New Statistical Pattern Recognition Technology for Condition Assessment of Cable-stayed Bridge on Earthquake Load |
Authors |
허광희(Heo, Gwanghee) ; 김충길(Kim, Chunggil) |
DOI |
https://doi.org/10.12652/Ksce.2014.34.3.0747 |
Keywords |
통계적 패턴인식 기술;관리차트;마할라노비스 거리;개선된 마할라노비스 거리;구조물상태모니터링 Statistical pattern recognition technology;Control chart;Mahalanobis distance;Improved mahalanobis distance;Structural health monitoring |
Abstract |
Earthwork in a large construction project such as a land development generally costs 20-30% of the total cost. The earthmoving process, comprising of four repetitive tasks: loading, hauling, unloading, returning, is quite simple and it does not need delicate or advanced techniques. Therefore, earthmoving earthwork planning can heavily affect the cost and time., and Even a slight deviation from the plan can increase or decrease the cost and time. This study presents a planning model that minimizes average haul distance in a large complex construction project. Based on earthwork planning, practitioners' heuristics, a districting algorithm and Simulated Annealing algorithm were employed to build the model. Districting algorithm plays a role that divides in dividing an earthmoving area into several sections. Simulated annealing provides a function that decides whether a new generated solution is confident. Finally, the proposed model was applied to a real earthmoving project of a large land development. It was found that the model showed approximately 14% improvement in average hauling distance compared to the actual design plan. |