An Adaptive Fuzzy Particle Swarm Optimization (AFPSO) based on the uncertainty of the PSO is proposed.
根据粒子群算法中的不确定性因素，提出自适应模糊的粒子群优化算法(AFPSO)。
Desgined a mixed intelligent arithmetic by using the technique of combing the stochastic simulation with fuzzy simulation and particle swarm optimization algorithm to solve this kind of problems.
基于粒子群算法运用随机模拟和模糊模拟相结合的技术，给出了一种求解该规划模型的混合智能算法。
Aimed at the disadvantages of fuzzy C-means in fault diagnosis of steam turbine set, a weighted fuzzy clustering method based on particle swarm optimization is put forward.
针对模糊c -均值算法在汽轮机故障诊断中的不足，提出了粒子群优化加权模糊聚类分析的方法。
Recently, Particle Swarm optimization is applied into function optimization, Neural Networks, data mining, Fuzzy Control System and other application field.
目前微粒群算法已广泛应用于函数优化、神经网络训练、数据挖掘、模糊系统控制以及其他的应用领域。
Recently, Particle Swarm optimization is applied into function optimization, Neural Networks, data mining, Fuzzy Control System and other application field.
目前微粒群算法已广泛应用于函数优化、神经网络训练、数据挖掘、模糊系统控制以及其他的应用领域。
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