资源列表
BP_PID
- 神经网络PID控制的阶跃响应，能够准确跟踪输入信号，各项指标满足要求。-the step response of Neural network PID control,Can accurately track the input signal, the indicators meet the requirements.
matlab
- 随机森林模型matlab仿真代码，能流畅运行哦-Random forests model of matlab code, and can run smoothly
RAN
- 基于RAN 改进的RBF神经网络代码，动态增加隐节点数，一种比较经典的改法-Based on the RAN improved RBF neural network
BPmoxing
- 动态神经网络时间序列预测研究——基于MATLAB的NARX实现-Dynamic neural network time series prediction- based on MATLAB realization NARX
TPLPSO
- 基于教与学改进机制的粒子群算法，对算法的精度具有积极的促进作用，对优化算法的学习具有帮助-Particle swarm optimization based on teaching and learning mechanism has a positive role in the accuracy of the algorithm,and is helpful in the study of optimization algorithms.
gm11
- 传统的GM（1,1）模型，适合测绘专业的学生用于研究灰色模型-The traditional GM (1,1) model for mapping majors gray model for research
mianyichengxu
- 免疫算法无功优化，很给力，自己认真学习即可-Immune algorithm
k_clique
- k_clique is matlab code to clique the tree problem
PCANet_demo
- pcanet 多层的pca 组成的网络，包含demo-pcanet 多层的pca 组成的网络
fpGrowth
- 经典FP-tree 算法的优化，纯python 实现，适用于频繁模式的挖掘和关联规则的发现-Optimization of classical FP-tree algorithm, pure Python implementation, suitable for mining frequent pattern and association rule discovery
gabasedonmatlab
- ga 基于matlab，遗传算法，两点交叉，二进制编码，可显示中间过程。-ga based on matlab
M-PSO
- 在粒子群算法的基础上进行改进的动态粒子群寻优算法，对于动态环境可以完成有效寻优，跟踪动态极值-On the basis of improved particle swarm optimization dynamic particle swarm optimization algorithm for dynamic environment optimization can be done effectively, track dynamic extremes