The design of a fuzzy-neural network for ship collision avoidance

  • Authors:
  • Yu-Hong Liu;Xuan-Min Du;Shen-Hua Yang

  • Affiliations:
  • Merchant Marine College of Shanghai Maritime University, Shanghai, China;Shanghai Marine Electronic Equipment Research Institute, Shanghai, China;Merchant Marine College of Shanghai Maritime University, Shanghai, China

  • Venue:
  • ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
  • Year:
  • 2005

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Abstract

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.