In this paper, several swarm intelligence optimization algorithm were applied in solving path planning problem in different fields.
本文将二者结合起来，研究了群智能优化算法在不同领域中路径规划规划问题的应用。
This dissertation makes deeply research on the Mean Shift, Particle Filter (PF), Unscented Particle Filter and intelligence optimization algorithm. And some beneficial results are obtained.
本论文在均值偏移、粒子滤波、无迹粒子滤波及智能优化算法等方面进行了较为深入的研究，取得了一些有益的成果。
The swarm intelligence optimization algorithm include: ant colony optimization algorithm, particle swarm optimization algorithm, artificial bee colony algorithm and artificial fish swarm algorithm.
目前提出的群智能优化算法有蚁群优化算法、粒子群优化算法、人工鱼群算法、人工蜂群算法。
Ant Colony algorithm is a novel simulated evolvement algorithm solving complicated combinatorial optimization problem and its typical feature is swarm intelligence.
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。
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。
Particle Swarm Optimization as a Swarm Intelligence algorithm, has strong global search capability, can be used for training neural network to overcome the defect of BP algorithm.
然而在粒子群优化算法中，早熟现象时有发生，从而制约了算法的性能。
PSO algorithm is a novel random optimization method based on swarm intelligence which has more powerful ability of global optimization.
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。
The basic and typical algorithm of swarm intelligence is particle swarm optimization and Ant colony oprimation.
目前，群智能理论研究领域有两种主要的算法：微粒群优化算法和蚁群优化算法。
A new algorithm of swarm intelligence, Particle swarm Optimization (PSO), which is an algorithm of simple implementation and fast convergence with few parameters, is introduced in this paper.
介绍了一种新的集群智能算法-微粒群算法(PSO)，该算法具有实现简单、参数少且收敛快的特点。
Optimization algorithm based on the swarm intelligence is a simulated evolutionary method that simulating the behaviors of social insects searching for food and building of nest.
基于群集智能的优化算法是一种仿生自然界动物昆虫觅食、筑巢行为的模拟进化算法。
Particle Swarm Optimization(PSO)algorithm is one of embranchments of swarm intelligence.
粒子群优化算法是群体智能中一个新的分支。
Based on the swarm intelligence, Particle swarm optimization (PSO) algorithm is a kind of modern optimization method inspired by the research of the artificial life.
粒子群算法是基于群集智能、受到人工生命研究结果的启发而提出的一种现代优化方法。
The algorithm mostly includes the tradition math optimization means, such as linear layout, nonlinear layout, mixed integral layout means, dynamic layout means, and artificial intelligence algorithm.
目前，无功优化方法主要有线性规划法，非线性规划法，混合整数规划法，动态规划法等传统的数学优化方法，以及人工智能优化算法。
As a representative swarm-intelligence based optimization algorithm, Particle SwarmOptimization (PSO) algorithm is applied to capacitor optimization in the dissertation.
微粒群优化算法（PSO）是目前备受关注的群集智能算法的代表性方法，也是本文研究工作的算法基础。
Ant Colony Optimization (ACO) algorithm is a new swarm intelligence heuristic algorithm.
蚁群算法是一种新兴的群智能算法。
As a swarm intelligence algorithm, AFSA has its weakness, such as high complexity, low optimizing precision and low convergence speed in the later period of the optimization.
但是作为一种新的群智能算法，人工鱼群算法有自身的不足，如算法的复杂度高、算法后期的收敛速度慢和收敛精度低等。
Tool-path airtime optimization during multi-contour processing in leather cutting is regarded as generalized traveling salesman problem. A hybrid intelligence algorithm was proposed.
将皮革裁剪多轮廓加工空行程路径优化问题归结为广义旅行商问题，提出了一种求解问题的混合智能优化算法。
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。
At present, there are many methods which are used for the optimal capacitor placement, such as Classical Optimization Algorithm, Artificial Intelligence and Hybrid Algorithm.
目前有多种配网无功规划优化方法，可分为传统优化算法、智能优化算法和混合法。
At present, there are many methods which are used for the optimal capacitor placement, such as Classical Optimization Algorithm, Artificial Intelligence and Hybrid Algorithm.
目前有多种配网无功规划优化方法，可分为传统优化算法、智能优化算法和混合法。
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