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.
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.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献