Research And Application Of Hybrid Water Wave Optimization Algorithm

Water Wave Optimization(WWO)[1]is a new heuristic optimization intelligent algorithm proposed in recent years.By the study of shallow water wave theory,scholar Zhang is inspired to simulate the three kinds of motion modes of water wave propagation,broken waves and refraction,so that water waves can search for motion in the search space,thus searching for a meta-inspiration of the optimal solution.Algorithm.WWO algorithm has better performance,but the water wave optimization algorithm itself is easy to fall into local optimum,premature convergence and so on.Therefore,considering the introduction of improved genetic operator,combined with the advantages of genetic algorithm and water wave optimization algorithm,a new type of proposed The hybrid algorithm mode makes the hybrid algorithm have better search ability,improves the convergence speed of search accuracy,and can also avoid falling into local optimum.In this paper,five kinds of functions are used to verify the hybrid algorithm,and compare it with other algorithms to verify the effectiveness of the hybrid algorithm.At the same time,the hybrid algorithm is applied to the image matching problem,which improves the efficiency of image matching.The main work has the following two points:First,In this paper,a new hybrid algorithm model of water wave optimization algorithm and genetic operator is proposed.Firstly,the water wave optimization algorithm and the genetic operator itself are improved.The chaos optimization strategy is introduced to the water wave optimization algorithm to reduce the influence of the initial population on the optimization performance of the algorithm.At the same time,the adaptive parameter update mechanism is combined to further improve the algorithm.The genetic operator itself is improved and an adaptive value based on fitness value is proposed.The strategy,while improving the genetic operator itself,has a better improvement in the performance of the entire hybrid algorithm.Finally,the comparison of experimental results with several general examples shows that the hybrid algorithm has better performance and can better balance the local and global search capabilities.It also proves that the construction and improvement of the hybrid algorithm is feasible and its performance.The simpler water wave optimization algorithm is more efficient;Finally,based on the image matching problem,the image matching method based on GAWWO is designed.The simulation results show that the proposed algorithm has faster image matching rate and higher matching precision,which greatly improves the image matching efficiency.While solving the image matching problem,it fully demonstrates the practicability and effectiveness of the hybrid algorithm in solving practical problems.