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Applying Neural Networks and Geographical Information Systems to Airport Noise Evaluation

  • Yingjie Yang
  • David Gillingwater
  • Chris Hinde
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3498)

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.

Keywords

Neural Network Geographical Information System Fuzzy Membership Aircraft Noise Aircraft Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yingjie Yang
    • 1
  • David Gillingwater
    • 2
  • Chris Hinde
    • 3
  1. 1.Centre for Computational IntelligenceDe Montfort UniversityLeicesterUK
  2. 2.Transport Studies Group, Department of Civil and Building EngineeringLoughborough UniversityLoughboroughUK
  3. 3.Department of Computer ScienceLoughborough UniversityLoughboroughUK

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