该文通过对现有群体智能理论和聚类算法的研究，提出了一种基于群体智能理论的聚类模型，并在此基础上给出了一种优化蚁群聚类算法。
This paper provides a model of the clustering and an optimized ant colony-clustering algorithm which is based on the swarm intelligence and that mathematic model is provided at the same time.
蚁群算法是一种新颖的求解复杂组合优化问题的模拟进化算法，它具有典型的群体智能的特性。
Ant Colony algorithm is a novel simulated evolvement algorithm solving complicated combinatorial optimization problem and its typical feature is swarm intelligence.
基于群体进化的智能优化算法在求解过程中存在计算效率低和易于早熟收敛等缺点。
Colony evolution based intelligent optimization algorithms have deficiencies of poor computational efficiency and are prone to premature during the solution process.
粒子群优化(PSO)算法是基于群体智能理论的优化算法。
Particle swarm Optimization (PSO) algorithm is based on swarm intelligence theory.
通常将这样一种模拟群居性生物中的集体智能行为的智能计算或优化方法称为群体智能算法。
Usually, we call the intelligence computation or optimization method that simulates swarm intelligence behavior of gregarious colony as Swarm Intelligence Algorithms.
粒子群优化算法是群体智能中一个新的分支。
Particle Swarm Optimization(PSO)algorithm is one of embranchments of swarm intelligence.
PSO算法是一种新型的基于群体智能的随机优化算法，简单易于实现且具有更强的全局优化能力。
PSO algorithm is a novel random optimization method based on swarm intelligence which has more powerful ability of global optimization.
粒子群优化算法(PSO)作为一种群体智能算法，它为复杂优化问题的解决提供了一种新的思路。
As a swarm intelligence algorithm, particle swarm optimization (PSO) algorithm has provided a new way to find the solution of complex problems.
粒子群优化(PSO)算法是一种基于群体智能的启发式搜索方法，应用领域很广。
Particle swarm optimization (PSO) is a heuristic search method based on swarm intelligence, and has been widely used to solve various problems in engineering fields.
粒子群优化(PSO)算法是一种基于群体智能的启发式搜索方法，应用领域很广。
Particle swarm optimization (PSO) is a heuristic search method based on swarm intelligence, and has been widely used to solve various problems in engineering fields.
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