遗传算法求解TSP问题

《游戏编程中的人工智能技术》一书中123章源代码- Game programming in artificial intelligence technology, one source book, Chapter 123

基于SVM，分本分类，，是关于两类分类的比较好的工具，国外网站提供，效果很好的-based SVM, the sub-classification is on the classification of the two types of relatively good tool, overseas sites provide good results, the

神经网络与遗传算法结合，需要的朋友就不用多说了，仅供学习和参考。-Neural network and genetic algorithm combined with the need for friends goes without saying, for learning and reference.

多层神经网络的可执行例子 http://www.codeproject.com/cpp/MLP.asp?df=100&forumid=148477&exp=0&select=1141594#xx1141594-multilayer neural network executable examples http :// www.codeproject.com/cpp/MLP.asp df = 1

TSP算法，应用局部搜索法得到最优路径，已经经过优化。没有密码，可以使用，vc环境下使用。-TSP algorithm, using local search to be optimal path has been optimized. No password can be used, vc environments.

对于具有一定规模的TSP问题的求解，至今没有较完善的求解办法。本程序是用遗传算法来求解TSP问题。-for a certain size of the TSP solution and there has been no better way to solve. This procedure is used genetic algorithms to TSP.

这是用VC编程实现模糊控制来控制机器人的运动-The misty control imitate really

基于k均值聚类学习算法的rbf神经网络实现-K-means clustering-based learning algorithm of rbf neural network

　人工神经网络(Aartificial Neural Network，下简称ANN)是模拟生物神经元的结构而提出的一种信息处理方法。早在1943年，已由心理学家Warren S.Mcculloch和数学家Walth H.Pitts提出神经元数学模型，后被冷落了一段时间，80年代又迅猛兴起［1］。ANN之所以受到人们的普遍关注，是由于它具有本质的非线形特征、并行处理能力、强鲁棒性以及自组织自学习的能力。其中研究得最为成熟的是误差的反传模型算法(BP算法，Back Propagation)，它的网络结构及算法直观、简单，在工业领域中应用较多。-Artificial Neural Networks (Aartificial Neural Network, under the short title of ANN) is a simulation of the structure of biological neurons and the information put forward a method of treatment. At early 1943, by Warren S. Mcculloch psychologists and mathematicians Walth H. Pitts proposed mathematical model of neurons, was left out in the cold for some time, and the rapid rise of the 80" s [1]. ANN because the general concern of the people is the essence of it is because of the non-linear characteristics of parallel processing capabilities, strong robustness and self-organizing capacity of self-learning. Research one of the most sophisticated are the error-propagation model of the algorithm (BP algorithm, Back Pro

免疫优化计算、学习与识别,是焦李成著的一本经典书中的源程序,供大家学习!-Immune Optimization calculation, learning and recognition, JIAO Li-cheng book is a classic source book for everyone to learn!