Referred to the character of particle swarm optimization and immune network theory, an immune particle swarm network algorithm for multimodal function optimization is proposed.
针对多峰函数优化问题，借鉴粒子群优化特性和免疫网络理论，提出一种免疫粒子群网络算法。
The simulative experimental results show that it has obvious improvement in multimodal function optimization problems with the case of the average run time reduced to 56% of the former.
仿真实验的结果也表明该算法在平均运行时间减少了56%的情况下多峰函数的优化效果得到了显著改善。
It makes a searching for all local optimization of the multimodal function that a PSO algorithm based on chaos sequence for multi-modal function optimization.
基于混沌序列的多峰函数微粒群寻优算法的目标就是找到多峰函数的所有局部优化峰值。
Particle Swarm optimization (PSO) algorithm is a population-based global optimization algorithm, but it is easy to be trapped into local minima in optimizing multimodal function.
粒子群优化算法应用于多极值点函数优化时，存在陷入局部极小点和搜寻效率低的问题。
Aimed at particle swarm optimization (PSO) algorithm being easily trapped into local minima value in multimodal function, a rotating surface transformation (RST) method was proposed.
针对粒子群优化算法(PSO)应用于多极值点函数易陷入局部极小值，提出旋转曲面变换(RST)方法。
Aimed at particle swarm optimization (PSO) algorithm being easily trapped into local minima value in multimodal function, a rotating surface transformation (RST) method was proposed.
针对粒子群优化算法(PSO)应用于多极值点函数易陷入局部极小值，提出旋转曲面变换(RST)方法。
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