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Real-time predictive analytics to estimate air traffic flow rates

机译:实时预测分析估算空中流量流速

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A Big data Analytics Infrastructure Testbed (BAIT) has been developed with the concept of providing analytics-as-a-service for algorithm developers to use when creating and testing new capabilities for air traffic management decision support. These capabilities typically require considerable processing power and must be tested and compared with a variety of algorithm modifications and parameter adjustments before they are incorporated into an existing real-time infrastructure. The BAIT infrastructure that has been developed and demonstrated has many applications, including: (1) Easily-configurable testing of multiple versions of the same algorithm simultaneously with automatic load balancing (2) Real-time and faster-than-real-time metrics generation providing the ability to alert air traffic flow managers of upcoming issues such as predicted flow rate limitations due to approaching weather (3) Rapid web-based display generation for the demonstration of real-time analytics and metrics This paper provides a description of the BAIT architecture, an initial use case and computational timing comparison, and a description of BAIT's web browser-based demonstration display.
机译:已经开发了一个大数据分析基础架构(诱饵)的概念,为算法开发人员提供了用于算法开发人员的概念,以在创建和测试空中交通管理决策支持的新功能时使用。这些功能通常需要相当大的处理能力,并且必须在将各种算法修改和参数调整中进行测试并进行比较,并且在将它们结合到现有的实时基础架构之前。已经开发和演示的诱饵基础设施具有许多应用,包括:(1)同时使用自动负载平衡(2)实时和比实时度量的多个算法的多种版本的多种版本的可配置测试提供能够警告由于接近天气(3)基于Web的基于Web的显示生成的预测流量限制等问题的空中流量限制,用于演示实时分析和度量,本文提供了对诱饵架构的描述,初始用例和计算定时比较,以及诱饵的基于Web浏览器的演示显示的描述。

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