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颗粒群
1、particle beam───粒子束，[高能]粒子束流
2、swarm───v.成群来回移动；蜂拥而至；挤满；爬；（蜜蜂）成群飞离蜂巢；n.一大群；蜂群；人群；一大群小型天体同时在空中出现
3、swarm with───挤满，充满；充满；挤满
4、god particle───上帝粒子
5、microbe swarm───微生物群
6、particle crossword───粒子纵横字谜
7、feel swarm───感觉蜂群
8、swarm app───swarm应用程序
9、particle───n.颗粒；[物]质点；极小量；小品词
1、Theory analysis of particle swarm optimization is always an important research topic.───微粒群算法的理论分析一直是其研究的难点。
2、Particle swarm Optimization (PSO) algorithm is based on swarm intelligence theory.───粒子群优化(PSO)算法是基于群体智能理论的优化算法。
3、Task assignment problem is a typical NP problem. Particle Swarm Optimization (PSO) algorithm was used to solve task assignment problem.───任务指派问题是典型NP难题，引入粒子群优化算法对其进行求解。
4、In this paper, we review ant colony algorithm and particle swarm optimization.───本文讨论了群集智能的两种算法，蚁群智能与微粒群智能。
5、To this problem, this paper proposed one kind of method to choose the parameters of the SVM by particle swarm optimization algorithm (PSO).───针对此问题，提出一种基于粒子群优化算法的支持向量机参数选择方法。
6、Classification is one tasks of data mining, using particle swarm optimization in classification especially classification rule extraction.───分类是数据挖掘研究的主要内容之一，将微粒群算法应用于分类问题，进行分类规则的提取。
7、It used to solve the problem that Particle Swarm Optimization(PSO) easily falls into a local extremum.───克服了经典粒子群算法中参数选择问题以及粒子群算法易陷入局部极值问题。
8、Particle swarm optimization is an extremely simple algorithm that seems to be effective for optimizing a wide range of functions.───粒子群优化是一个非常简单的算法，似乎是有效的优化了广泛的职能。
9、Particle swarm algorithm was an optimized algorithm based on swarm intelligence.───粒子群算法是一类基于群智能的随机优化算法。
1、Compared with the real data, particle swarm neural network with sliding time window technique in modeling the mid and long term electric load is effective, and the model can meet the actual demands.
2、The results have shown the effectiveness of particle swarm optimization for flexible job shop scheduling.
3、An improved immune particle swarm optimization was presented in this study in order to increase the effectiveness of feature selection for emotion recognition based on Galvanic Skin Response (GSR).
4、For locating the critical failure surface, the particle swarm or the harmony method is used, which is an upper bound approach.
5、An algorithm for discretization based on Particle swarm optimization (PSO) is presented, which can settle the problem of continuous attributes discretization in systema modeling perfectly. ?
6、A new improved discrete particle swarm optimization algorithm is designed to tackle the Traveling Salesman Problem.
7、A cultural-based particle swarm optimization (CBPSO) algorithm is proposed to improve the computational accuracy and efficiency of PSO and avoid premature.
8、Particle swarm optimized particle filter (PSOPF) incorporates the newest observations into sampling process and also optimizes it.
9、A modified particle swarm optimization algorithm for nonlinear system identification is presented.