Research On Ships Collision Based On Particle Swarm Optimization

In recent years, with the number of ships increasing and ships'weights growing, navigation security issues are increasingly important. How to ensure the safety of ships sailing is an urgent need to resolve. At the same time, many experts and scholars are studying the emphasis.Reasonable ways to ships collision avoidance and the suitable determines of ships collision avoidance are the guarantee of the safety navigation. Firstly, this thesis gives the ways of ships collision avoidance by particle swarm optimization (PSO) algorithm and other two improved PSO algorithm. Then considering the determination of ships collision risk is a very complex process, and it is affected by many factors. Also, it has a strong feature of the nonlinear. Based on the features of PSO algorithm and the neural network, this thesis constructs the model of neutral network. It is verified through function fitting, classification and general XOR problem. At last, this model is applied to determination of ships collision avoidance.The main research results in this thesis can be summarized as follows:(1) The ways of ships collision avoidance are, respectively, determined by PSO algorithm, improved chaotic PSO algorithm and improved immunity PSO algorithm, and the simulation is done with a target ship, two and three goals in various encounter posture. In comparison with the exhaustive law, it is improved that the three algorithms can achieve better results, and it can be applied to determination of ways of ships collision avoidance.(2) The model of neural network based on PSO algorithm is constructed. Considering the random of the number of the hidden layers and the determination of weight for BP neural network, firstly, this model utilizes hybrid particle swarm optimization to optimize the structure and initial weights for the neural network, and then training by BP. Its performance is mainly through the binary PSO algorithm to determine the threshold of the neutral network and decimal PSO algorithm to determine the neurons number of the hidden layers.(3) Function fitting, Iris classification, Wine classification, LED classification and general XOR problem are used to verify the performance of neural network based on PSO algorithm. The computing results show that the model can achieve better results.(4) Determines the ships collision risk through the model of neural network based on PSO algorithm. Simulated by the sample data of two actors and six actors respectively, the results show that the model can achieve better results.