神经网络与免疫算法的结合，用matlab编程实现小功能

函数的遗传算法优化程序-function of genetic algorithm optimization procedures

C++神经网络开发包,基于C++语言，VisualC++环境-C++ Neural network development package, based on the C++ Language, VisualC++ Environment

贝叶斯算法是基于贝叶斯定理 P(H|X) = P(X|H)P(H) / P(X).。对于多属性的数据集，计算 P(X|Ci) 的开销非常大，为减低计算复杂度，我们做条件独立的假设，即给定元组的类标号，假定属性值有条件地相互独立，即在属性间不存在依赖关系。此程序仅为算法的一个实现，根据训练数据训练分类器-Bayesian algorithm is based on the Bayes theorem P (H | X) = P (X | H) P (H)/P (X).. For multi-attribute data sets, computing P (X | Ci) of the overhead is very large, in order to reduce the computational complexity, we do conditional independence assumption that a given tuple class label, it is assumed that property values conditionally independent of each other, that does not exist in the inter-attribute dependencies. This procedure is only an implementation of algorithm, according to training data classifier training

利用空间表示的rcc8模型进行空间推理， 解决csp问题，可以自动产生csp问题，然后解决，利用了不同的算法并且做了比较，有仿真试验。-said that the use of space rcc8 model spatial reasoning, problem solving csp. csp can be generated automatically, and then resolved, the use of different algorithms and made a comparison, a simulation test.

基本蚂蚁算法及其改进算法求解NP问题的论文汇总，而且全是中文，对于初学者一定有帮助-The basic ant algorithm and its improved algorithm for solving NP problems summary papers, and they are all Chinese, will certainly be helpful for beginners

遗传算法解决双变量的函数最优化问题，有按钮的界面，用bc所编，生动模拟遗传进化过程-genetic algorithm to solve the two- variable optimization function, the button interface, using bc prepared by the vivid simulation of the process of genetic evolution

遗传算法求解的程序，非常好用。适合建模问题的求解。-Genetic algorithm procedure is very easy to use. Suitable model for solving the problem.

模拟3G环境，测试可伸缩视频码流，适合JSVM开发者-Analog 3G environment, testing, scalable video stream, suitable for JSVM developers

针对TSP问题，用类神经网路的方法去求解！-against TSP, and the neural network approach to solving!

详细介绍了SVM 和RVM的区别及各自的优点，说明RVM在很多方面优于SVM-Described in detail the difference between SVM and the RVM and their respective advantages, indicating RVM in many ways superior to SVM