资源列表
interruptible-load-calculation
- 本MATLAB程序是基于离散粒子群算法的可中断负荷的优化计算-The MATLAB program is a discrete particle swarm optimization algorithm based on interruptible load calculation
ABL
- 基于元胞自动机编写的传染病扩散matlab代码，为了运行方便，把所有代码都集中在了一个m文件中，重要部分都带有注释，算法取得了较好的结果，在这里分享给大家。- Cellular Automata based infectious disease diffusion write matlab code, in order to facilitate operation, all the codes are concentrated in an m file, important parts a
chengxutu
- 混沌粒子群优化算法，有测试函数，可以直接运行，对研究不同混沌映射的粒子群算法有帮助-Chaos particle swarm optimization algorithm, the test function can be directly run, the study of the particle swarm algorithm with different chaotic map help
FastSLAM
- fastslam的程序，十分全，毕设用过了，研究生毕业论文也用了。-fastslam procedures, very full, complete set used, and graduate thesis also used.
using-GA-in-antenna-array
- 提出了整数编码，动态调整交叉概率、变异概率，并将适应度函数设为最大相对旁瓣电平,一种改进遗传算法的优化方法来实现直线稀疏阵列的设计-Proposed integer coding, dynamic adjustment of crossover probability, mutation probability, and the fitness function is set to the maximum relative sidelobe level, an improved genetic
Quantum-particle-cluster-algorithm
- 量子粒子群的聚类算法，一种新的数据聚类算法，用于数据聚类，和k均值聚类，和粒子群聚类比较有更好的效果-Quantum particle cluster algorithm
NSGA-II(matlab程序)
- 基于多目标优化的遗传算法，非常适合parato逼近运算
sijiache
- 私家车充电模型，私家车日行驶距离概率密度及累加函数，电动汽车出发时间（或者称开始充电的时间）概率-Private car charging model, private car day driving distance probability density function and cumulative electric vehicle departure time (or start charging of said time) probability
xitong7tongbu
- 滑膜控制，实现滑模同结构控制以及分数阶与整数解的同步-Synovial control, synchronization with structure sliding mode control and Fractional and Integer Solutions
PSO_AI
- 免疫粒子群算法的matlab源代码，自己设置优化函数-Immune particle swarm algorithm matlab source code, set up their own optimization function
NSGA2
- 基于非支配排序的带有精英策略的多目标优化算法:NSGA-II,测试函数是DTLZ-Based on the non-dominated sorting multiobjective optimization algorithm with elitist strategy: NSGA-II, the test function is DTLZ
nine_bus_pf
- 使用simulink仿真，实现潮流计算。。。非常详细，可以对学习潮流计算和simulink的提供帮助。 -Use simulink simulation, realization flow calculation. ʱ ?? ʱ ?? Very detailed, can help to study the trend of computing and simulink.