To solve a class of non-differentiable optimization problems, this paper proposed a new method called maximum-entropy particles swarm optimization algorithm.
针对一类不可微优化问题，本文提出了一个新的算法—极大熵微粒群混合算法。
Aiming at the stagnation exists in the cooperative particle swarm optimization, presents a new kind of the cooperative particle swarm optimization algorithm based on particles spatial extension.
针对协同微粒群优化存在的停滞现象，提出了一种新的基于粒子空间扩展的协同微粒群优化算法。
This paper presents swarm optimization algorithm based on a pair of parallel particles, which can be used to get a good codebook in the vector quantization of image coding.
本文提出一种粒子群分组并行寻优码书设计算法，应用于图像的矢量量化编码中，它可以得到性能较好的码书。
The standard particle Swarm optimization (PSO) algorithm cannot adapt to the complex and nonlinear optimization process, because the same inertia weight is used to update the velocity of particles.
由于标准粒子群优化(PSO)算法把惯性权值作为全局参数，因此很难适应复杂的非线性优化过程。
The standard particle Swarm optimization (PSO) algorithm cannot adapt to the complex and nonlinear optimization process, because the same inertia weight is used to update the velocity of particles.
由于标准粒子群优化(PSO)算法把惯性权值作为全局参数，因此很难适应复杂的非线性优化过程。
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