原文传递
Operational Dynamic Configuration Analysis
| 题名： | Operational Dynamic Configuration Analysis |
| 作者： | Lai, Chok Fung; Zelinski, Shannon |
| 关键词： | rational；operation；analysis；dynamic；onfi；urat；threshold；clusterin；baseline；distribution |
| 摘要： | Sectors may combine or split within areas of specialization in response to changing traffic patterns. This method of managing capacity and controller workload could be made more flexible by dynamically modifying sector boundaries. Much work has been done on methods for dynamically creating new sector boundaries [1-5]. Many assessments of dynamic configuration methods assume the current day baseline configuration remains fixed [6-7]. A challenging question is how to select a dynamic configuration baseline to assess potential benefits of proposed dynamic configuration concepts. Bloem used operational sector reconfigurations as a baseline [8]. The main difficulty is that operational reconfiguration data is noisy. Reconfigurations often occur frequently to accommodate staff training or breaks, or to complete a more complicated reconfiguration through a rapid sequence of simpler reconfigurations. Gupta quantified a few aspects of airspace boundary changes from this data [9]. Most of these metrics are unique to sector combining operations and not applicable to more flexible dynamic configuration concepts. To better understand what sort of reconfigurations are acceptable or beneficial, more configuration change metrics should be developed and their distribution in current practice should be computed. This paper proposes a method to select a simple sequence of configurations among operational configurations to serve as a dynamic configuration baseline for future dynamic configuration concept assessments. New configuration change metrics are applied to the operational data to establish current day thresholds for these metrics. These thresholds are then corroborated, refined, or dismissed based on airspace practitioner feedback. The dynamic configuration baseline selection method uses a k-means clustering algorithm to select the sequence of configurations and trigger times from a given day of operational sector combination data. The clustering algorithm selects a simplified schedule containing k configurations based on stability score of the sector combinations among the raw operational configurations. In addition, the number of the selected configurations is determined based on balance between accuracy and assessment complexity. |
| 报告类型： | 科技报告 |
相关文献
- Vehicle Corrosion Expert System (CES)
- Structural Health Monitoring of I-10 Twin Span Bridge - Part I: Analysis of Lateral Load Test, Tech Summary.
- Instrumentation of the US Grant Bridge for Monitoring of Fabrication, Erection, In-Service Behavior, and to Support Management, Maintenance, and Inspection.
- Overview of Dynamic Airspace Configuration.
- Computer-Based Dynamic and Finite Element Analysis of the Joint Services Imagert Processing System (JSIPS) Trailer; Modified M871A1, 22 1/2 Ton, Flatbed, Semi-Trailer
- Comparing Methods for Dynamic Airspace Configuration.
检索历史
应用推荐
