搜索资源列表
mfiles
- 1) Automated Gram-staining characterization of digital bacterial cell images 2) Classification of bacteria based on set of contour features
37724100frog
- 细菌觅食优化算法 ，解决比例积分控制器参数优化的程序，对初学细菌算法很有帮助。-Bacterial foraging optimization algorithm to solve PI controller parameter optimization procedure, useful for beginners bacterial algorithm.
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.
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。
BCC
- 粒细菌群优化算法的matlab实现版本，在原有算法基础上作了必要的修正-Particle swarm optimization algorithm matlab bacterial realized version of the original algorithm made the necessary corrections on the basis of
bacterial-foraging-algorithm
- 基于细菌觅食算法的函数优化分析Function optimization analysis based on bacterial foraging algorithm-Function optimization analysis based on bacterial foraging algorithm
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
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
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)
细菌觅食算法
- 一个用MATLAB实现的细菌觅食优化算法(A bacterial foraging optimization algorithm using MATLAB)
BG-PSO
- 细菌吞噬算法程序，可以在matlab上运行(Bacterial phagocytosis algorithm program)
BFO
- 细菌觅食算法程序，实现细菌觅食基本功能，找寻最优解。大神们可以自行修改。(Bacterial foraging algorithm is used to realize the basic function of bacteria foraging and find the optimal solution.)