这是一个非常好用的蚂蚁算法(蚁群算法)模拟程序,很好用噢,快来试试吧...

遗传算法的c语言程序-Genetic Algorithm c Language Program

分类器的设计，包括knn方法和BP的方法。对一系列样本点进行分类-Classifier design, including methods and BP KNN method. On a series of sample points to classify

RBF程序，可实现函数拟合，本人已经亲自调试过，效果不错。-RBF procedures can realize function fitting, I have personally debugging, and good results.

这是书上的常用搜索算法，有8数码游戏，黑白棋，A star算法类的实现。-This is a book commonly used search algorithm, there are 8 digital game, Reversi, A star algorithm category realize.

　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

很好的神经网络教程，里面包含源代码，可以进行相关的修改!-Good neural network tutorial, which contains the source code, can be related to changes!

Mitchell的《机器学习〉随书源码，非常不错-Mitchell"s "machine learning> With the source book, very good

用遗传算法求解背包问题是南京航空航天大学信息与计算科学专业编写的.本程序利用遗传算法来求解背包问题.采用二进制字符串编码,1表示选择物体,0则不选择. 背包问题描述:在M件物品取出若干件放在空间为W的背包里，每件物品的重量为W1，W・2……Wn，与之相对应的价值为P1,P2……Pn。求出获得最大价值的方案。注意：在本题中，所有的重量值均为整数。-genetic algorithm knapsack problem is the Nanjing University of Aeronautics and Astronautics, Information and Computing Science prepared. The procedure the use of genetic algorithms to solve knapsack problem. binary string encoding, an option objects, 0 no choice. Knapsack Problem Description : M items removed several pieces on the space-W backpack, Each of the weight W1, W 2 ... Wn, the corresponding value of P1, P2 ... Pn. Sought to gain maximum value of the program. NOTE : In this issue, all the weight values are integers.

本人调试的大作业（源程序模型+论文），主要包括PID控制、模糊控制、神经网络控制、遗传算法优化神经网络控制（使用了遗传工具箱GAOT）对同一系统所作的仿真比较，并加入饱和、死区、时滞等非线性后的响应，具体的分析比较过程论文中写的很详细。-I debug a big operation (source model+ Thesis), including PID control, fuzzy control, neural network control, genetic algorithm optimization of neural network control (using a genetic toolbox GAOT) on the same system simulation by the comparison, and to join saturation, dead zones, such as nonlinear time-delay after the response, the specific analysis of the comparison process paper written in great detail.

神经网络的HP算法，这是神经网络入门的好程序-HP neural network algorithm, this neural network is a good entry procedures