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

Authors :
Yeung, Daniel S.
Zhi-Qiang Liu
Xi-Zhao Wang
Hong Yan
Yu-Hong Liu
Xuan-Min Du
Shen-Hua Yang
Source :
Advances in Machine Learning & Cybernetics; 2006, p804-812, 9p
Publication Year :
2006

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540335849
Database :
Supplemental Index
Journal :
Advances in Machine Learning & Cybernetics
Publication Type :
Book
Accession number :
32901505
Full Text :
https://doi.org/10.1007/11739685_84