Study on Adaptability of Several Optimization Algorithms Used in Evaluation Flatness Error
In order to evaluate the flatness error quickly and accurately.The flatness error evaluation model is estab-lished.The seagull optimization algorithm is improved.The particle swarm optimization algorithm,firefly and particle swarm optimization algorithm,atom search optimization algorithm,seagull optimization algorithm and improved seagull algorithm are applied to evaluate the flatness error.The boundary factor is introduced to control the search range,and a series of boundary factor values are set to evaluate the flatness error of eight samples by the above five optimization methods.The adaptability of the five algorithms in flatness error evaluation is studied from three aspects,calculation accuracy,efficiency and the influence of boundary factor.Some evaluation results are displayed graphically.The results show that the atomic search optimization algorithm has the worst adaptability and the lowest calculation accuracy among the five algorithms,and the flatness error value fluctuates the most with the increase of the boundary factor value,and it is not easy to set the appro-priate boundary factor in application.The improved optimization algorithm in the flatness error evaluation,has the highest precision flatness error,and it is less affected by the boundary factor value,computational efficiency is higher,which consid-ering algorithm accuracy,efficiency and boundary factor,the influence of five kinds of algorithms of flatness error evaluation of the best algorithm adaptability.
万方数据
维普
