Optimization the Layout of Airport Noise Monitoring Points Based on Gray Dynamic Neural Network Model

Author:

Ding Jian Li1,Yang Zhao Hui1

Affiliation:

1. Civil Aviation University of China

Abstract

The key of airport noise monitoring is the appropriate layout of airport noise monitoring points. In this paper, we bring out an optimization algorithm based on the advantages of gray dynamic neural network model in the network training and fitting operations. We use it with the airport noise prediction contour map from INM software to optimize the present layout of airport noise monitoring points in a large domestic hub airport. Experiment results show that the experimental layout of monitoring points program can reflect the distribution of airport noise.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference7 articles.

1. Margreet Beuving and Brian Hemsworth, in: Improved Methods for the Assessment of the Generic Impact of Noise, Environment Final Synthesis Report (2007), pp.33-36.

2. Yue Jianping, in: Gray dynamic neural network model and its application to dam safety monitoring, volume 34 of Journal of Hydraulic Engineering 2003, pp.120-123.

3. Yingjie Yang, Chris Hinde and David Gillingwater, in: Airport Noise Simulation Using Neural Networks, International Joint Conference on Neural Networks (2008), p.1917-(1923).

4. Information on http: /www. faa. gov.

5. Tim P. Vogels, Kanaka Rajan and L.F. Abbott, in: Neural Network Dynamics, volume 28 of Annual Review of Neuroscience (2005), pp.357-376.

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