论文标题
通过机器学习帮助减少航空的环境影响
Helping Reduce Environmental Impact of Aviation with Machine Learning
论文作者
论文摘要
商业航空是气候变化的最大贡献者之一。我们建议通过考虑减少飞行时间的解决方案来减少航空的环境影响。具体来说，我们首先考虑改善高空预测，以便飞行计划者可以使用更好的信息来查找有效的路线。其次，我们提出了一种飞机路由方法，该方法试图通过考虑风预测中的不确定性，然后在勘探和开发之间进行最佳交易来找到通往目的地的最快路线。
Commercial aviation is one of the biggest contributors towards climate change. We propose to reduce environmental impact of aviation by considering solutions that would reduce the flight time. Specifically, we first consider improving winds aloft forecast so that flight planners could use better information to find routes that are efficient. Secondly, we propose an aircraft routing method that seeks to find the fastest route to the destination by considering uncertainty in the wind forecasts and then optimally trading-off between exploration and exploitation.
