元胞自动机的matlab代码，CA procedures

用人工神经网络实现异或的功能。用反向传播算法（BP）来实现神经网络，正确率可以达到80% -using artificial neural network XOR functions. With back-propagation algorithm (BP) to achieve neural network, can achieve an accuracy rate of 80%

最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector machines using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999. -The newest work tools of svm,it will be very convenient to have it.

通用的蚁群算法，这个算法可以高效地解决tsp问题-Common ant colony algorithm, this algorithm can efficiently solve the problem tsp

矩形件排样优化问题是一个多目标优化问题，另一方面要考虑到生产时的下料效率-Rectangular pieces of nesting optimization problem is a multi-objective optimization problem, on the other hand, taking into account the production efficiency of the next expected

介绍了神经网络模式识别的基本知识，适合于模式识别领域的人员-it introduces the ABC of the pattern recognation of NN, it is for the people of pattern recognation

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

微粒群算法与其它进化类算法相类似，也采用“群体”与“进化”的概念，同样也是依据个体（微粒）的适应值大小进行操作。所不同的是，微粒群算法不像其它进化算法那样对于个体使用进化算子，而是将每个个体看作是在n维搜索空间中的一个没有重量和体积的微粒，并在搜索空间中以一定的速度飞行。-Particle swarm optimization algorithm with other similar type of evolution, but also the use of " groups" and " evolution" concept is also based on the individual (particle) size of the operation of fitness. The difference is that unlike other particle swarm optimization evolutionary algorithm as the use of evolution for the individual operator, but as each individual in the n-dimensional search space of a weight and size of the particles, and in the search space the speed of a certain flight.

条码技术-barcode technology

林火预测元胞自动机的代码，利用它可以对未来的林火情况进行模拟和预测-Forest Fire Cellular Automata prediction code, using it for the future forest fire situation in the modeling and prediction

人工智能动物推理系统程序-animal AI reasoning system procedures