搜索资源列表
ACOpID
- 寻优控制参数，利用新型算法，模仿大自然生物觅食行为的蚁群算法，在MATLAB环境下进行仿真实验，寻优PID控制参数。-Optimizing control parameters, using a new algorithm that mimics the natural biological foraging behavior of ant colony algorithm, simulation experiments in the MATLAB environment, optimizing
BFA(MATLAB)
- 细菌觅食算法（BFA算法）的MATLAB源代码，Word文档，可作为最优解的仿生算法使用，对研究人员有帮助。-Bacterial foraging algorithm (BFA algorithm) MATLAB source code, Word documents, can be used as the optimal solution using bionic algorithm, for researchers to help.
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
biomimicry-of-bacterial-foraging
- 最早提出细菌觅食算法的经典之作。biomimicry of bacterial foraging for distributed optimization and control-the firstly proposed paper about bacterial foraging optimization named biomimicry of bacterial foraging for distributed optimization and control。
PSO
- 粒子群优化算法(PSO) 也是起源对简单社会系统的模拟。最初设想是模拟鸟群觅食的过程。但后来发现PSO是一种很好的优化工具。-Particle Swarm Optimization (PSO) is also the origin of a simple social system simulation. Originally conceived simulated birds foraging process. But later found PSO is a good optimizatio
pso
- 粒子群优化算法(Particle Swarm optimization,PSO)又翻译为粒子群算法、微粒群算法、或微粒群优化算法。是通过模拟鸟群觅食行为而发展起来的一种基于群体协作的随机搜索算法。通常认为它是群集智能 (Swarm intelligence, SI) 的一种。它可以被纳入多主体优化系统(Multiagent Optimization System, MAOS).粒子群优化算法是由Eberhart博士和kennedy博士发明。-PSO (Particle Swarm optimiz
Particle-swarm-optimization
- 粒子群算法（ Particle Swarm Optimization, PSO）最早是由Eberhart和Kennedy于1995年提出，它的基本概念源于对鸟群觅食行为的研究。-Particle swarm optimization (Particle Swarm Optimization, PSO) was first proposed in 1995 by the Eberhart and Kennedy, it stems from the basic concept study fora
A-novel-bacterial-foraging
- 一种新型细菌觅食算法 采用协搜索策略 一种新型细菌觅食算法 采用协搜索策略-A novel bacterial foraging technique for edge detection
Advanced-Bacterial-Foraging
- 改进的细菌觅食算法 能较好的改善原来的缺点 -A new co-bacterial foraging algorithm search strategy
pfo
- 用于求解函数优化问题的细菌觅食算法，java源代码-Bacterial foraging algorithm for solving function optimization problems, java source code
pso-algorithm
- 通过模拟鸟群觅食行为而发展起来的一种基于群体协作的随机搜索算法。-The basic particle swarm optimization algorithm
DAIMA
- 细菌觅食算法改进，改进传统细菌觅食的局部最优现象。同时引入最优解丢失寻回功能-Bacterial foraging algorithm improvements
AFSA
- 一个基本的人工鱼群算法，包括追尾行为、聚群行为、觅食行为随机行为等的一个可在matlab7.0上运行出来的算法-An algorithm running out on a basic matlab7.0 AFSA, including rear-end behavior of clusters acts of random behavior of foraging behavior
pso_func
- 混沌粒子群的优化算法,最早是在模拟鸟群觅食过程中的迁徙和群集行为时提出的一种基于群体智能的进化计算技术。（已改进）-Chaos particle swarm optimization algorithms, the first is a cluster of movement and foraging behavior of birds in the simulation process when the proposed evolutionary computing technique bas
Ant-Colony-Algorithm
- 用于人工智能，模仿蚂蚁觅食，以提高数据计算效率-For Artificial Intelligence, imitating foraging ants to enhance the efficiency of data calculation
鱼群算法---代码
- 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，以下是鱼的几种典型行为: (1)觅食行为：一般情况下鱼在水中随机地自由游动,当发现食物时,则会向食物逐渐增多的方向快速游去。 (2)聚群行为:鱼在游动过程中为了保证自身的生存和躲避危害会自然地聚集成群，鱼聚群时所遵守的规则有三条：分隔规则：尽量避免与临近伙伴过于拥挤;对准规则
fishswarm
- 鱼群算法，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-Fish swarm algorithm, c language programming, in the midst of the waters, the fish tend to fish on their own or trailing other nutrients fo
code
- 粒子群优化算法:是通过模拟鸟群觅食行为而发展起来的一种基于群体协作的随机搜索算法。-Particle Swarm Optimization
bfcc
- 细菌觅食聚类程序Bacterial foraging clustering-Bacterial foraging clustering
BFA
- MATLAB编写的细菌觅食优化算法的源程序-Bacterial foraging algorithm for solving function optimization problems .MATLAB source code