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。
The most difficult task in analysis of landslide lies in search of critical slide plane. Intelligence optimization arithmetic has its own spectacular advantage in solving this type issue.
滑坡分析最困难的问题在于临界滑动面的搜索，智能优化算法在解决此类问题时有着独特的优势。
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。
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。
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。
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。
Regarding the workshop technique of manufacture, the swarm intelligence algorithms are used to solve the facility layout optimization problem.
对于车间制造技术，论文使用群智能算法求解车间的设备布局优化问题。
The present research constructs a wireless sensor network coverage optimization strategy based on swarm intelligence.
本文基于群体智能建立无线传感器网络的覆盖优化策略。
As a new type of searching method for global optimization, Genetic algorithms has some merits such as intelligence searching, parallel mode, robust and wide application.
遗传算法作为一种新的全局优化搜索方法，具有智能性搜索、并行式计算、鲁棒性强、应用范围广等优点。
Usually, we call the intelligence computation or optimization method that simulates swarm intelligence behavior of gregarious colony as Swarm Intelligence Algorithms.
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。
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。
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。
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。
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。
SAS campaign management, analytics, optimization and reporting capabilities can be utilized because of the integration with SAS Customer Intelligence.
因为SAS客户智能的集成，SAS活动管理，分析，优化和报告功能可以利用。
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。
Version 4.0 includes the option for optimization of refrigerant circuitry based on computational intelligence methods.
版本4.0包括制冷剂的选择优化回路基于计算智能方法。
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。
In modern times, the rapid development of artificial intelligence technology has provided a strong theoretical foundation on solving optimization scheduling problem.
近代人工智能技术的飞速发展对于解决优化调度问题提供了有力的理论基础保障。
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。
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。
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。
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。
应用推荐