资源列表
Desktop
- 经典的主成分算法 还有及其改进的RPCA 等等算法 都是核心程序 用户只要把数据加载进入就可以用-Classical PCA algorithm and its improved algorithms are the core program RPCA so long as the data is loaded into the user can use
fit
- 文化算法。利用MATLAB编写的文化搜素算法-Culture Algorithm
tsp
- 本程序为神经网络解决TSP问题 数据有100城市 200城市和500城市，采用VC++编程 程序中已经设置成最佳参数 交叉驴0.6 变异率0.01 @ 迭代500 代。效果不错-The procedures for the neural network to solve the TSP data of 100 cities 200 cities and 500 cities, using VC++ programming procedure has been set to the optim
bp00
- bp神经网络vc++实现,具有较好的效果，可以参考-bp neural network vc++ realize, with good results, you can refer to
apriori
- 先验概率算法--apriori.包括频繁项的查找和关联分析的算法。具体请参看源码。-Priori probability algorithm- apriori. Including frequent finding and association analysis algorithms. Please refer to the specific source.
GDFNN_operator
- 将训练数据，训练数据的输入量个数作为函数的输入，将网络拟合输出，泛化输出-The training data, the training input data as a function of the number of input, output network fitting, generalization output
yichuansuanfaqiujie
- 根据选择的遗传算法编写程序，步骤很详细，完整的小程序-Genetic algorithm based on the selected programming, steps are detailed and complete applet
yichuansuanfa
- 遗传算法种群初始化，通过GDFNN训练得到优化结果-GA population initialization, optimization results obtained through GDFNN training
shenjingwangluo
- 可以根据不同训练数据，采用GA自适应求解对应的GDFNN初始参数优化值。-According to different training data, using adaptive solution corresponding GDFNN GA initial parameters optimized values.
mohukongzhic
- 以下本人从修改的模糊控制代码，经过自己修改后可在vc6.0，运行！输入e表示输出误差，ec表示误差变化率，经过测试具有很好的控制效果，对于非线性系统和数学模型难以建立的系统来说有更好的控制效果！-I have the following code from a modified fuzzy control, through their modifications in vc6.0, run! Enter e represents the output error, ec represents t
SVM_GUI_3.1[mcode]{by-faruto}
- 由faruto写的一个最新的svm工具箱，希望对大家有用-faruto write a new svm toolbox, I hope useful to you！
GRNN-
- 基于广义回归神经网络的数据预测，使用交叉验证的GRNN神经网络预测程序，包含BP和GRNN效果比较程序。两网络用相同的数据进行训练。-Based on generalized regression neural network data prediction, using cross-validation GRNN neural network prediction program, including BP and GRNN effect comparison procedures. Two