A study on the collision avoidance of a ship using neural networks and fuzzy logic

被引：128

作者：

Ahn, Jin-Hyeong

Rhee, Key-Pyo ^{[1
]}

You, Young-Jun ^{[1
]}

机构：

[1] Seoul Natl Univ, Coll Engn, Dept Naval Architecture & Ocean Engn, Seoul 151, South Korea

来源：

APPLIED OCEAN RESEARCH | 2012年 / 37卷

关键词：

Collision avoidance system; Collision risk; ANFIS (Adaptive Network-based Fuzzy Inference System); MLP (Multilayer Perceptron); DOMAINS;

D O I：

10.1016/j.apor.2012.05.008

中图分类号：

P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

In this this paper, the fuzzy inference system combined with an expert system is applied to collision avoidance system. Especially, calculation method of the collision risk by using neural network is proposed. At first, the membership functions of DCPA and TCPA are determined on the basis of simulation results using the KT equations. And then, the inference table is redesigned by using the ANFIS (Adaptive Network-based Fuzzy Inference System) algorithm. Secondly, additional factors, the ship domain, topological characteristics and restricted visibility, which can affect navigator's reasoning of the collision risk besides DCPA and TCPA are considered. Finally, MLP (Multilayer Perceptron) neural network to the collision avoidance system is applied to make up for fuzzy logic. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：162 / 173

页数：12

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