基本遗传学习分类系统算法，算法结构非常严谨，是不可多得的遗传算法！...

Dynamic Programming Code for the TSP

BugBots是一个游戏，描述它的最好方式是它是一个测试人工智能的框架。 来源: http://sourceforge.net/projects/bugbots/-BugBots is a game, describing it as the best method is that it is a test of artificial intelligence framework. Source : http://sourceforge.net/projects/bugbots/

人工智能课程习题与解答-artificial intelligence programs to answer the questions and

web流数据聚类挖掘的研究和应用。流数据作为一种特殊的可挖掘的数据类型，特别是基于网络技术迅速发展的今天，其彰显出的重要地位决定了它的挖掘技术需要被认真考虑，而如何在流数据中进行有效的聚类分析，是一个吸引研究者很大注意力的问题。-Clustering web streaming data mining research and applications. Flow data as a special type of data that can be excavated, in particular the rapid development of Web-based technology today, it underlines the important status of the decision of its mining technology need to be seriously considered, and how to stream data effectively together type of analysis, is a great to attract the attention of researchers question.

Biome是一个c++库，它的目的是个人_基于代理的模拟器（象 Swarm 或EcoSim）。它试图尽可能达到高效并且同时有好的设计-PROJECT is a c library, it is aimed at individual _ Agent-based simulator (like Swarm or EcoSim). It seeks to achieve efficient as possible while it is good design

这是一个有关于模式识别中的isodata算法的matlab源码。 大家可以看看。有详细注释-on the isodata pattern recognition algorithm Matlab source. We can look at. Detailed Notes

height 遗传身高计算 根据父母的升高计算后代身高-height

调用过程 CM = Confusion_matrix(train_predicts, train_targets) [combining_predicts, errorrate] = combining_NB(DP, test_targets, CM) DP，三维数组，(i,j,k)为第k个样本的DP矩阵 targets 为 0 1 2 -process called CM = Confusion_matrix (train_predicts, train_targets) [combining_predicts, errorrate] = combining_NB (DP, test_targets, CM) DP, three-dimensional array (i, j, k) for the k samples of DP matrix targets for 0 1 2

遗传算法的四个源程序和源代码，在国内没有过的，看看国外的程序员是怎么编写的-Four genetic algorithm source code and source code, never at home and abroad to see how the programmer is prepared

自组织系统Kohonen网络模型。对于Kohonen神经网络，竞争是这样进行的：对于“赢”的那个神经元c，在其周围Nc的区域内神经元在不同程度上得到兴奋，而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程，经过一定次数的训练以后，网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构：它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ ..