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How can we be smarter in aircraft noise quantification and management?

机译：我们如何在飞机噪声量化和管理中更聪明？

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After many years of measurement and modelling, the management of aircraft noise seems as difficult as ever. On some sites, complaints have become more frequent in spite of an overall decrease in aircraft noise. This leads us to question whether we are measuring or modelling the right quantities. Managing aircraft noise is a multi-dimensional problem for which no simple solution has been found. In this paper we explore some of the issues that appear to be significant, such as the accumulation in time of different short-term metrics. Neural network methods provide new insight into the proper quantification of noise from different source types. Training of neural networks for aircraft noise classification presents some special problems, which will be illustrated at the oral presentation.
机译：经过多年的测量和建模，飞机噪音的管理似乎与以往一样困难。在某些地方，尽管飞机噪音总体下降，投诉已经变得更加频繁。这使我们能够质疑我们是否正在测量或建模正确的数量。管理飞机噪声是一个多维问题，没有找到简单的解决方案。在本文中，我们探讨了一些似乎很重要的问题，例如不同短期指标的时间累积。神经网络方法提供新的洞察来自不同源类型的正确量化。飞机噪声分类的神经网络培训具有一些特殊问题，将在口头呈现中说明。

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