...由于早熟现象难以准确计算最优分割阈值,因此导致图像分割准确率低。为了提高图像分割准确率且准确地提取出图像目标,提出一种基于混沌粒子群算法(CPSO)的图像阈值分割方法。受益于混沌运行的遍历性、对初始条件的敏感性等优点,CPSO很好地解决了PSO的粒子群过早聚集和陷入局部最优等...
基于6个网页-相关网页
为了有效地解决水火电力系统资源短期优化调度问题，提出了一种基于混沌粒子群算法的调度方案。
To solve hydrothermal power system resource short-term optimization scheduling problem, this paper proposed a novel scheduling solution based on chaos particle swarm optimization algorithm.
文章把混沌优化搜索技术引入到P SO算法中，提出了基于混沌搜索的粒子群优化算法。
This paper incorporates chaos optimization algorithm into the PSO algorithm, and propose a new particle swarm optimization algorithm based on chaos searching (CPSO).
应用粒子群优化算法(PSO)求解电力系统无功优化问题，提出基于混沌搜索的混合粒子群优化算法，以克服P SO容易早熟而陷入局部最优解的缺点。
The chaos search based hybrid particle swarm optimization (PSO) algorithm is proposed in the paper to avoid the premature phenomenon of PSO, which is applied into the reactive power optimization.
应用推荐