搜索资源列表
Bacterial-foraging-algorithm
- 基于细菌觅食算法的优化计算的matlab程序实现-Bacteria foraging optimization algorithm based on the calculation of the matlab program implements
AF_algrithm
- 在一片水域中,鱼往往能自行或尾随其他鱼找到营养物质多的地方,因而鱼生存数目最多的地方一般就是本水域中营养物质最多的地方,人工鱼群算法就是根据这一特点,通过构造人工鱼来模仿鱼群的觅食、聚群及追尾行为,从而实现寻优。-In the midst of the waters, the fish often can be found on their own or trailing other fish nutrients in many places, so that the largest numbe
Bacterial-Foraging-Computer-Program
- 细菌觅食MATLAB算法,可以直接运行,推荐推荐-Bacterial foraging MATLAB algorithms can be run directly, recommended recommended
anti_TSP
- 蚁群算法是一种智能优化算法,通过介绍蚁群觅食过程中基于信息素的最短路径的搜索策略,给出基于MATLAB的蚁群算法在旅行商问题中的源代码m文件,对问题求解进行局部优化。-Ant colony algorithm is an intelligent optimization algorithm through the shortest route of pheromone search strategy based on the ant foraging process, given the ant
MOPSO-MATLAB
- 多目标粒子群算法是模拟动物群体的社会行为,找到一个最优设计点的过程比作这些生物的觅食活动。换句话说,这些例子在设计空间中寻找最好的位置。-Multi-objective Particle Swarm social behavior is simulated animal groups, a process to find the optimal design point likened foraging activity of these organisms. In other words, t
BFO
- 细菌觅食优化算法函数分析及matlab代码实现-Bacteria foraging optimization algorithm function analysis and the realization of matlab code
BG-QPSO
- 基于细菌觅食的量子行为粒子群算法,已试验,可运行-Quantum Behavior Particle Swarm Optimization (QPSO) algorithm based on bacterial foraging has been tested and run
DWT_bof
- 细菌觅食算法在人脸识别中的应用,图像经过小波变换预处理-The application of bacterial foraging algorithm in face recognition, image preprocessing by wavelet transform
matlabaoc
- 自1991年由意大利学者 M. Dorigo,V. Maniezzo 和 A. Colorni 通过模拟蚁群觅食行为提出了一种基于种群的模拟进化算法——蚁群优化。-ant colony optimization, ACO
12pso-algorithms
- 粒子群算法,也称粒子群优化算法或鸟群觅食算法(Particle Swarm Optimization),缩写为 PSO-Particle swarm optimization (PSO), also known as particle swarm optimization (PSO) or PSO (Particle Swarm Optimization)
CGIFBN
- C source code BFO细菌觅食算法改进优化算法-C source code BFO bacterial foraging algorithm improved optimization algorithm
bfo
- 一个基于细菌觅食优化算法求解多目标问题的算例,提供参考-A bacterial foraging optimization algorithm based on multi-objective numerical examples, reference
基于人工鱼群算法的一元非线性函数寻优
- 人工鱼群算法是受鱼群行为的启发,由李晓磊等人于2002年提出的一种基于动物行为的群体智能优化算法。在一片水域中,鱼往往能自行或尾随其它鱼,找到营养物质最多的地方,因而鱼生存数目最多的地方一般就是本水域中营养物质最丰富的地方。人工鱼群算法根据这一特点,通过构造人工鱼来模仿鱼群的觅食、聚群、追尾、随机行为,从而实现寻优。本代码是基于人工鱼群算法的一元非线性函数寻优。
细菌优化算法
- 细菌觅食算法 可以用来解决电力系统无功优化,调度等寻优问题,可以来参考下(Bacterial foraging algorithm can be used to solve the power system reactive power optimization, scheduling and other optimization problems, you can refer to)
ABC_MATLAB_web
- 一种模拟蜂群觅食的算法,人工蜂群算法,可以用于参数寻优(artificial beem calculation)
MOALO
- 根据蚁狮觅食行为启发而提出的一种群智能搜索算法,并进行标准函数测试,效果较好(A swarm intelligence according to the foraging behavior of ant lion heuristic search algorithm, and the standard test function, good effect)
pso粒子群算法matlab代码
- 粒子群算法,也称粒子群优化算法或鸟群觅食算法,优化算法,用于对目标的最优值算法(optimization algorithm)
garterial-algorithm-BFO
- C source code BFO细菌觅食算法改进优化算法(C source code BFO bacterial foraging algorithm improved optimization algorithm)
ABC_MATLAB_web
- 蜂群借鉴蜜蜂觅食机制,用于函数优化、组合优化(ARTIFICIAL BEE COLONY ALGORITHM)
pso
- 粒子群算法,也称粒子群优化算法或鸟群觅食算法(Particle Swarm Optimization),缩写为 PSO。它具有精度高,收敛快等优点,广泛用于系统辨识、函数优化等领域。文件pso.m是粒子群算法辨识程序,在此基础上,需要自行编写目标函数计算程序以实现不同系统的参数辨识。(Particle swarm optimization (PSO), also known as particle swarm optimization algorithm or bird swarm foragi