资源列表
feed
- 结合模糊评价和bp神经网络将网路权值转换成个因素的权重 Combining fuzzy evaluation and BP neural network to transform the weights of network weights into factors(Combining fuzzy evaluation and BP neural network to transform the weights of network weights into factors)
reinforement.tar
- 强化学习grid python代码，使用的算法为动态规划，很好的入门强化学习的例子(reinforement grid study.)
ANN_fitting_example_1
- ANN fitting，使用多层神经网络对某一个函数进行插值逼近，建立代理模型(ANN fitting. Using a multi-layer neural network to interpolate a certain function to establish a proxy model)
sa
- 利用模拟退火法解决污染源识别，主要解决一维水质模型的溯源问题。(identification of pollutant source)
bp
- 双隐层反向传播神经网络，预测,分析均方根误差误差,数据包传送源码程序。(It is a double hidden layer back-propagation neural network, future line prediction, analysis error, data packet transmission source program.)
renkouyuce_test002
- 用NAR神经网络预测未来几年的人口数量变化趋势(Forecasting the changing tendency of population in several years by NAR Neural Network)
八数码问题
- 八数码问题也称为九宫问题。在3×3的棋盘，摆有八个棋子，每个棋子上标有1至8的某一数字，不同棋子上标的数字不相同。棋盘上还有一个空格，与空格相邻的棋子可以移到空格中。(Eight digital problems)
xgBoost_Intro
- python xgboost分类程序的例子，需安装xgboost库。(An example of the python xgboost taxonomy requires the installation of the xgboost library.)
face-KNN
- 用PCA算法和KNN算法实现人脸识别，参数可以自己调整(The PCA algorithm and the KNN algorithm are used to realize the face recognition, and the parameters can be adjusted by themselves)
RBF_NN_MIC
- 可以用于多输入单输出的RBF径向基神经网络建模。。(The RBF neural network can be used to creat the model,which can be descrided by multi input and one output)
digital
- 实现手写体识别，并且使用自己手写的数字作为验证，得到了比较好的结果(digital recognition we get a good result at the test of our own digital writing and use the language of pyton)
kmeans1
- 实现k-means算法的matlab代码(the matlab code of the k-means algorithm)