Applying neural networks and geographical information systems to airport noise evaluation

  • Authors:

  • Yingjie Yang;David Gillingwater;Chris Hinde

  • Affiliations:

  • Centre for Computational Intelligence, De Montfort University, Leicester, UK;Transport Studies Group, Department of Civil and Building Engineering, Loughborough University, Loughborough, UK;Department of Computer Science, Loughborough University, Loughborough, UK

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
  • Year:
  • 2005

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Abstract

The assessment of aircraft noise is becoming an increasingly important task in ensuring sustainable airport development. Aircraft noise is influenced by many complex factors and traditional laboratory models are not sufficient to assess the exposure to noisy flights of specific local communities in proximity to an airport. In this paper neural network and fuzzy set methods have been integrated with Geographical Information Systems to provide an alternative method to evaluate airport noise.