Ship navigation safety risk assessment based on genetic algorithm and BP neural network


Ship navigation safety risk assessment based on genetic algorithm and BP neural network


He Zhang1*, Zhuyun Shao1, Ji Zeng1

1Shanghai Maritime University, Shanghai 201306, China.


Scientific Research and Reviews

In order to ensure the safe navigation of ships and reduce the occurrence of marine accidents, through the analysis of ship historical navigation safety accident data and related accident literature research, taking into account various aspects such as marine meteorology, cargo loading, ship status and crew quality. Construct a ship navigation safety evaluation body. The BP neural network algorithm is used to design the ship navigation safety risk network structure. The sea damage data is used as the network input sample to train the BP neural network and data fitting. At the same time, the genetic algorithm is introduced to find the individual corresponding to the optimal fitness, and the weight and threshold of the network are further optimized. The purpose is to improve the accuracy of data fitting. The optimized BP neural network evaluation results show that there are many indicators affecting the safety of the ship’s navigation, and the relationship between the indicators is complicated. The optimized BP neural network utilizes the characteristics of online adaptive learning, which eliminates the construction of complex relationships among various indicators within the structure, and solves the difficult problems in ship risk assessment to a certain extent.


Keywords: Ship navigation safety; BP neural network; Genetic algorithm; Risk assessment


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How to cite this article:
He Zhang, Zhuyun Shao, Ji Zeng. Ship navigation safety risk assessment based on genetic algorithm and BP neural network. Scientific Research and Reviews, 2020; 13:117. DOI:10.28933/srr-2020-08-1505


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