Route Planning Of Ship Based On Improved Wolf Pack Algorithm

With the rapid development of modern science and the rapid progress of human civilization,maritime traffic is becoming increasingly busy.However,accidents such as collisions or stranding of ships bring a lot of harms such as the danger of the crew 's life,serious economic losses,and pollution to the environment.Therefore,it is vital to ensure the safety of maritime navigation.There is huge demand in researching on navigation path planning.Actually,the path planning process is an optimization process.At present,mature optimization algorithms such as particle swarm optimization,ant colony optimization,genetic algorithm,and simulated annealing algorithm are applied to various optimization problems.The wolf pack algorithm used in this paper is also an optimization algorithm.This algorithm has attracted widespread attention from many domestic and foreign experts and scholars due to its high accuracy,fast convergence,and good robustness.Wolf Pack Algorithm is a new bionic intelligent algorithm proposed based on the hunting behavior of wolves.This algorithm has been applied in many engineering fields due to its high performance.However,there is still room for optimization in terms of optimization efficiency and convergence accuracy.This paper's background is ship sailing on the surface.This paper uses improved wolf pack algorithm to optimize the problems in the path planning process.The specific research contents are as follows:1.Wolf pack algorithm and its improvement analysis.Firstly,this paragraph analyzes the principle and solution steps of the wolf pack algorithm in detail.Next,two improvements are proposed for the process of walking so that the improved wolf pack algorithm has better optimization efficiency and convergence accuracy than the original wolf pack algorithm.This algorithm is used as an optimization algorithm for LSTM network hyperparameters and an algorithm for path planning in this paper.Finally,this paragraph verify the improvement of this algorithm to the wolf pack algorithm by simulation.2.Deal with obstacles.The main research works of this paragraph include introducing the density peaking algorithm and its advantages and disadvantages,improving the existing deficiencies,building a prediction model of static obstacles,verifying the feasibility of the cluster algorithm,making a ship trajectory predicting system by improved wolf pack algorithm and deep studying model,building a sample generation system based on AIS data.3.Plan the path according to the processed obstacle information.The main research works of this paragraph include making a route planning system by improved wolf pack algorithm to avoid processed obstacles,comparing the difference of improved wolf pack algorithm,original wolf pack algorithm and classic artificial potential field algorithm by simulation,introducing the advantages of improved wolf pack algorithm.