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首页> 外文期刊>Journal of Guidance, Control, and Dynamics >Short-Term National Airspace System Delay Prediction Using Weather Impacted Traffic Index
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Short-Term National Airspace System Delay Prediction Using Weather Impacted Traffic Index

机译:使用受天气影响的交通指数进行的短期国家空域系统延误预测

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THE National Airspace System (NAS) has been studied both forrnidentifying the air traffic delaymodels and for improving the airrntraffic flow management efficiencies. Studies show that 70% of allrndelays in the NAS are related to weather and, of these, 60% arerncaused by convective weather [1]. For good weather days, factorsrnother than weather, including air traffic demand–capacityrnimbalances, equipment outages, and runway conditions also havernto be characterized. To guide flow control decisions and developrnstrategies to reduce delays, cancellations, and other costs during thernday of operations in variousweather conditions, it is useful to create arnreal-time delay predictionmodel and provide the delay prediction forrnseveral hours.
机译:已经对国家空域系统(NAS)进行了研究,以识别空中交通延误模型并提高空中交通流量管理效率。研究表明,NAS中70%的延迟都与天气有关,其中60%是由对流天气引起的[1]。在天气好的日子里,除了天气以外的其他因素,包括空中交通需求,容量失衡,设备中断和跑道状况,也都必须加以表征。为了指导流量控制决策并制定策略以减少在各种天气条件下运行期间的延迟,取消和其他成本,创建实时实时延迟预测模型并提供几个小时的延迟预测是有用的。

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