水波中心扩散智能优化算法

基于水波扩散效应，提出了一种水波中心扩散算法(water wave center diffusion,WWCD)。着眼解决函数极值优化问题，以某个局部最优解为中心点，由近至远、由密至疏产生多组扩散解进行迭代寻优。通过合理设计扩散解的扩散比例、选择比例和跳跃比例等参数，提高算法的全局寻优效率，对比WWCD与6种智能优化算法极值优化问题的仿真结果，验证了前者在全局求解精度和收敛速度方面的优越性。聚焦雷达信号识别问题，WWCD优化支持向量机(support vector machine,SVM)关键参数进行雷达信号识别实验。仿真结果表明，通过本算法优化SVM关键参数进行雷达信号识别，可明显提高识别效率。

Intelligent Optimization Algorithm Based on Water Wave Center Diffusion

Based on the diffusion effect of water waves, an intelligent optimization algorithm for water wave center diffusion (WWCD) is proposed. In order to solve function extreme value optimization problems, a local optimal solution is taken as the center point, and multiple sets of diffusion solutions are generated from near to far and from dense to sparse for iterative optimization. The global optimization efficiency of the algorithm is improved by reasonably designing the parameters such as diffusion ratio, selection ratio and jump ratio of the diffusion solution. The simulation comparison of the extremum optimization problem is carried out by using the water wave center diffusion optimization algorithm and six intelligent optimization algorithms, which verifies the superiority of the proposed algorithm in global solution accuracy and convergence speed. Focusing on the problem of radar signal recognition, the experiment of radar signal recognition is carried out by using the key parameters of support vector machine optimized by the water wave center diffusion algorithm. The simulation results show that the key parameters of support vector machine optimized by this algorithm can significantly improve the recognition efficiency.