The Design of a Fuzzy-Neural Network for Ship Collision Avoidance

  • Yu-Hong Liu
  • Xuan-Min Du
  • Shen-Hua Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)


A fuzzy-neural network for ship collision avoidance where ships are in sight of one another is proposed in this article. There are three subsets: the subset of classifying ship encounter situations and collision avoidance actions, the subset of calculating the membership functions of speed ratio, and the subset of inferring alteration magnitude and action time. The weight values of the former two subsets are obtained by self-learning from a number of samples, while those of the last subset are obtained from experience. The test results show that by the use of this network, some valuable decisions can be made.


Membership Function Hide Neuron Collision Avoidance Speed Ratio Target Ship 
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 2006

Authors and Affiliations

  • Yu-Hong Liu
    • 1
  • Xuan-Min Du
    • 2
  • Shen-Hua Yang
    • 1
  1. 1.Merchant Marine College of Shanghai Maritime UniversityShanghaiChina
  2. 2.Shanghai Marine Electronic Equipment Research InstituteShanghaiChina

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