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Research on Optimization of Ship Collision Avoidance Decision

摘要


Based on artificial intelligence technology and neural network calculation method, this paper summarizes the important factors that affect the ship domain model, and reasonably introduces them into the domain model as the input, and the ship domain size as the output, so as to obtain the scientific and reasonable quantitative boundary or the dynamic boundary adjusted immediately according to the function model. This paper systematically summarizes the risk quantification model and research results of ship collision avoidance decision optimization, comprehensively analyzes the results of collision avoidance decision model based on knowledge base, and constructs the evaluation model of ship collision avoidance decision optimization according to multi-objective genetic algorithm. Through the design of ship collision avoidance algorithm, we can plan a safe and short collision avoidance path, which not only ensures the safe navigation of the ship, but also reflects the ship's automatic collision avoidance intelligence. It has a certain practical significance for the research of ship collision avoidance system and algorithm.

參考文獻


Modeling of ship trajectory in collision situations by an evolutionary algorithm. R. Smierzchalski, Z. Michalewicz. IEEE Transactions on Evolutionary Computation. 2000.
Planning a Collision Avoidance Model for Ship Using Genetic Algorithm. Xiao-ming Zeng, Masanori. IEEE 2355-2360. 2001.
A Fuzzy Logic Method for Collision Avoidance in Vessel Traffic Service. Sheng-Long Kao, Kuo-Tien Lee, Ki-Yin Chang,Min-Der Ko. The Journal of Neuroscience. 2007.
Longhui Gang, Yonghui Wang, Yao Sun, et al. Estimation of vessel collision risk index based on support vector machine. 2016, 8(11):143-153.
Xiaoqin Xu, Xiaoqiao Geng, Yuanqiao Wen. Modeling of Ship Collision Risk Index Based on Complex Plane and Its Realization. 2016, 10(2):251-256.

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