本文研究了一个群g上的直觉l模糊子群。
In this paper, we study the intuitionistic L-fuzzy subgroups on a group g.
引入向量值模糊子集与向量值模糊子群的概念，并给出若干等价条件。
The concepts of VV fuzzy subset and VV fuzzy subgroup are introduced and some equivalent conditions are given.
给出未确知子群的定义和相应的定理，在此基础上，讨论未确知子群与模糊子群、一般子群的关系。
In this paper the definition and theorems of unascertained subgroup are introduced. And on this basis, the relationship between unascertained subgroup and fuzzy and general subgroup is discussed.
最后讨论了向量值正规模糊子群与向量值模糊商群的性质，同时建立了向量值模糊商群的同构定理。
Some properties of VV normal fuzzy subgroup and VV fuzzy quotient group are discussed and the isomorphism theorem of VV fuzzy quotient group is established.
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。
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.
模糊神经网络的学习算法采用的是快速的粒子群优化算法。
A fast stochastic global optimization algorithm, particle group optimization algorithm, was used for training the fuzzy neural network.
针对模糊c均值算法与粒子群算法的不足，提出了一种基于粒子群算法和模糊c—均值算法的混合聚类算法。
To avoid the shortcomings of FCM and Particle Swarm Optimization algorithm, new hybrid clustering algorithm based on PSO and FCM algorithm is proposed.
且改进的粒子群算法在模糊神经网络权值的训练中收敛速度和跳出局部最优的能力都要比BP算法更优。
And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.
为解决此问题，提出一种基于捕食-被捕食的粒子群优化模糊聚类算法且聚类中心采用密度函数初始化。
To solve the problem, a fuzzy clustering based on predator prey PSO algorithm is presented, which is using density function to initialize cluster centre.
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。
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.
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)。
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)。
An Adaptive Fuzzy Particle Swarm Optimization (AFPSO) based on the uncertainty of the PSO is proposed.
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