Research Of The Improved Algorithm Based On The Invasive Weed And Its Application

In recent years,the intelligent optimization algorithm has many advantages,such as good results,global,availability,and no need to understand the specific parameters,which is the focus of research workers in the field of computer technology,engineering design,transportation optimization,and has achieved great social repercussions.Intelligent optimization algorithm based on particle swai*m optimization algorithm,such as particle swarm,the invasion of weeds,etc,has taken more and more people's attention.However,there are still many problems in intelligent optimization algorithm,which is more and more complex,and the requirements of the performance of the algorithm ai*e also more and more high.Therefore,the design of a fast,robust,high accuracy,performance and stability of intelligent optimization algorithm is still an urgent research topic.In this paper,we improve the particle swarm optimization algorithm and the standard invasive weed algorithm,and apply the improved algorithm to the an*ay antenna pattern synthesis,and provide a new way to solve these problems.The main results of this paper are as follows:(1)In this paper,the algorithm is easy to fall into local optimization.The two algorithms are integrated into the hybrid algorithm,which is based on the hybrid algorithm.The algorithm is composed of population space and belief space.The algorithm is based on the framework of particle swarm optimization.The algorithm is based on the mechanism of particle swarm optimization,and the belief space is used to improve the efficiency of the algorithm.(2)It is still difficult to solve the problem of high dimensional competition based on the principle of multi-dimensional competitive culture.First,the algorithm uses the optimal point set theoiy,and improves the quality of the initial solution.Secondly,the algorithm is more prone to jump out of local optimum.Then,the improved algorithm is embedded into the cultural framework.Through the test of 5 classical test functions,the paper shows that the algorithm can not only converge quickly,but also get a lot of the ability to jump out of the local optimum.(3)A new solution is presented for the synthesis of array antennas.The improved algorithm is applied to the antenna array.The method is tested and the results are satisfactory.