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Predicting flight delays with artificial neural networks: Case study of an airport

机译:用人工神经网络预测航班延误:一个机场的案例研究

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Air transportation has an important place among transportation systems and it is indispensable for the flights to perform their voyages in scheduled time in order to ensure the comfort of passengers and controllability of operational costs. There are several reasons for flight delays like weather conditions, excessive intensity in air traffic, accidents or closed airfields, conditions that will lead to an increase in distances between planes and operational delays in ground services. In this study, using the data collected from the sensors located in the airport and the information about the flight, the goal is develop a machine learning model to estimate departure delays of flights using artificial neural networks.
机译:航空运输在运输系统中占有重要地位,对于确保乘客的舒适度和可控制的运营成本,航班必须在预定的时间进行航行是必不可少的。造成航班延误的原因有很多,例如天气情况,空中交通强度过大,事故或封闭的机场,这些情况会导致飞机之间的距离增加以及地面服务的延误。在这项研究中,利用从位于机场的传感器收集的数据和有关航班的信息,目标是开发一种机器学习模型,以使用人工神经网络估算航班的起飞延误。

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