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AFSA
- 人工鱼群算法是一种近年来提出的组合优化问题，该算法在收敛速度方面有明显的优势。并在现实的各个方面都已经开始应用。 -Artificial fish-swarm algorithm is a combinatorial optimization in recent years raised the issue in the convergence speed of the algorithm has an obvious advantage. And in reality, all aspec
Clerc_seminar_15122004
- Particle swarm optimization (PSO) was originally designed and introduced by Eberhart and Kennedy (Ebarhart, Kennedy, 1995 Kennedy, Eberhart, 1995 Ebarhart, Kennedy, 2001). The PSO is a population based search algorithm based on the simulation of
gamin
- 采用粒子群算法的参数辨识，计算速度更快，参数更准确。-Using particle swarm optimization algorithm parameter identification, computing faster, more accurate parameters.
01714200
- K-means Algorithm Based on Particle Swarm Optimization Algorithm for Anomaly Intrusion Detection
1
- During the last decade, many variants of the original particle swarm optimization (PSO) algorithm have been proposed. In many cases, the difference between two variants can be seen as an algorithmic component being present in one variant but
hybrid-GAaPSO.pdf.tar
- Novel hybrid genetic algorithm & particle swarm opitimization
Hybrid_PSO_entropy-15-01247-v2
- A Hybrid Chaos-Particle Swarm Optimization Algorithm for the Vehicle Routing Problem with TimeWindow
swarm-optimization-algorithm-
- 子群优化算法，并把次算法用于求解旅行商问题．为了增强算法的局部搜索能力，在改进的算法中加入倒置，局部搜索等方法，同时利用遗传算法的全局搜索能力强的特点对求到的解再进行优化，同时，对于搜索全局最优路径方面，通过应用消除交叉路径的方法进行了优化．-Sub swarm optimization algorithm, and the second algorithm is used to solve the traveling salesman problem. In order to enhance
The-new-meta-heuristic-algorithm-bat
- 摘要：新型元启发式算法例如粒子群算法，萤火虫算法，和声搜索算法已经成为现今复杂的优化问题的有效解决方法。该文基于蝙 蝠的回声定位行为提出了一种新型的元启发式算法———蝙蝠算法，同时也将现有的一些算法的优点引入到该算法中。 改文对该算 法进行了详细的公式化表述并对其执行流程的作出了说明，并且将该算法与遗传算法、粒子群优化算法等算法进行了比较。仿真结 果表明,蝙蝠算法明显优于其他算法，并对进一步的研究作出了展望。-Summary: The new meta-heuristic algor
A PSO-based algorithm designed for a swarm of mobile robots
- A PSO-based algorithm designed for a swarm of mobile robots
zl
- 描述鱼群的最优化问题，以及边际问题，包括觅食居群行为-Artificial fish swarm algorithm code to deal effectively optimize the optimization problem, with better optimization results than the genetic algorithm
xiaobobao
- 基于小波包的边缘检测，可以用于检测图片边缘，大小噪声的检测-Artificial fish swarm algorithm code to deal effectively optimize the optimization problem, with better optimization results than the genetic algorithm
Microgrid-optimization-algorithm
- 基于改进负荷密度法的微网负荷预测_王有春，基于改进粒子群算法的微网环保经济运行的优化_万术来，基于改进型快速寻优算法的微网经济负荷优化_胡龙龙_温向宇_黄焯麒-Improved load density law microgrid load forecasting based on _ Wang Youchun, based on improved particle swarm optimization algorithm Microgrid green economy run _ Wan su
Intelligent-algorithm
- 智能算法，包括粒子群，改进粒子群，改进遗传算法等，可用于预测等领域！-Intelligent algorithms, including PSO, improved particle swarm, improved genetic algorithm can be used to predict other fields!
mppt
- This paper proposes an improved maximum power point tracking (MPPT) method for the photovoltaic (PV) system using a modifi ed particle swarm optimization (PSO) algorithm.
cat-swarm-optimization
- In this paper, we present a new algorithm of swarm intelligence, namely, Cat Swarm Optimization (CSO). CSO is generated by observing the behaviors of cats, and composed of two sub-models, i.e., tracing mode and seeking mode, which model upon th
pso-based-pats-papr-ofdm
- A Suboptimal PTS Algorithm Based on Particle Swarm Optimization Technique for PAPR Reduction in OFDM Systems
estimation-extended-Kalman-filter
- 针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题，提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点，采用可调整的算法模型对粒子群算法进行改进，将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理，将优化后的卡尔曼滤波器应用于感应电机转速估计。- Extended K
A-combination-of-genetic-algorithm-and-particle-s
- A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems Distributed generation (DG) sources are becoming more prominent in distribution systems due to the incremental dema
Based-on-the-pso-of-PSO
- 本文描述的是用粒子群优化算法下的支持向量机的研究，详细概述了其优化参数-This article describes the algorithm under the support vector machine optimized by particle swarm optimization parameters detailed overview of its