BP-ANN

vit程序清晰简单，容易阅读，matlab调用易实现(vit procedures clear and straightforward, easy to read, matlab call easy to realize)

焦炉加热燃烧过程即时模型设计,把焦炉温度的实时数据生成温度曲线，实现了VC++与matlab的混合编程(Instant combustion process of coke oven model design)

这是一个matlab程序， G-P算法计算混沌信号关联维的 Matlab 程序 (This is a matlab program, GP algorithm to calculate the correlation dimension of chaotic signals Matlab program)

这里实现了基于四种SVM工具箱的分类与回归算法: 1、工具箱：LS_SVMlab Classification_LS_SVMlab.m - 多类分类 Regression_LS_SVMlab.m - 函数拟合 2、工具箱：OSU_SVM3.00 Classification_OSU_SVM.m - 多类分类 3、工具箱：stprtoolsvm Classification_stprtool.m - 多类分类 4、工具箱：SVM_SteveGunn Classification_SVM_SteveGunn.m - 二类分类 Regression_SVM_SteveGunn.m - 函数拟合 更详细的相关函数说明请通过help命令查看！(Here the realization of the four SVM toolbox based on the classification and regression algorithm: 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox: stprtoolsvmClassification_stprtool.m- Multiclass Classification 4 toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting a more detailed explanation of the correlation function through the help command to view!)

该程序用于将OMNI原始数据转换为mat格式的数据(The program for OMNI raw data is converted to the mat format data)

动态规划matlab程序，适用于只有一个状态变量的情况(dynamic programming matlab program that applies only to one state variable.)

matlab下可以直接使用的小程序 包括各种常用算法 对应书籍为《matlab宝典》 此为第四部分(matlab can be directly used for small programs include a variety of commonly used algorithms corresponding books as " matlab book" This is the fourth part)

MATLAB与fortran混编的案例代码，可运行，是学习的好例子(MATLAB mixed case with fortran code can be run, is a good example of learning)

In this paper, we introduce a new machine-learning-based data classification algorithm that is applied to network intrusion detection. The basic task is to classify network activities (in the network log as connection records) as normal or abnormal while minimizing misclassification. Although different classification models have been developed for network intrusion detection, each of them has its strengths and weaknesses, including the most commonly applied Support Vector Machine (SVM) method and the Clustering based on Self-Organized Ant Colony Network (CSOACN). Our new approach combines the SVM method with CSOACNs to take the advantages of both while avoiding their weaknesses. Our algorithm is implemented and evaluated using a standard benchmark KDD99 data set. Experiments show that CSVAC (Combining Support Vectors with Ant Colony) outperforms SVM alone or CSOACN alone in terms of both classification rate and run-time efficiency.

matlab gui 串口调试助手 能实时画图并保存数据(Matlab GUI serial debug assistant can draw and save data in real time)