这是一个Prolog程序，是我的同学做的，对于学Prolog的朋友有些帮助，希望大家多多交流。...

k均值聚类算法源码，比较经典，无解压密码-kmeans clustering algorithm source code,comparatively classical,no password for unzip

BP神经网络C＋＋实现-BP neural network implemented by C++

A star 算法类的实现(算法接口，针对迷宫问题设计)-algorithm to achieve the category (algorithm interface design issues against maze)

该工具包提供七种神经网络的C语言实现方式，对那些真正学习神经网络的人有一定的帮助和指导意义。-The kit provides seven neural networks realize the C language by means of neural networks to learn who the real people who have a certain degree of help and guidance.

基与多种智能方法和模式识别技术的研究,如果你也在从事相关研究,一定要看看,我想应该有借鉴价值-base with a variety of intelligent methods and pattern recognition techniques, but if you are engaged in related research, we must look at, I think there should be a reference value

使用线性分类器进行分类，采用感知器算法中的“奖惩算法”，各提取3类中的前25个样本共75个作为学习样本。-The use of a linear classifier for classification, perceptron algorithm using the reward and punishment algorithm , the extraction of 3 categories of the top 25 a total of 75 samples as the learning samples.

遗传算法人工生命模拟,这是一个遗传算法关于人工生命模拟的实例-Artificial Life Simulation of genetic algorithm, which is a genetic algorithm on the example of artificial life simulation

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.

本代码是人工智能中产生式的一个例子，功能是实现对有限动物特征识别的正向和反相推理。-the code is generated artificial intelligence-an example of that function is limited to the identification of the animal forward and inverse reasoning.

用BCB编写的Kohonen程序做优雅的网格分布，将任意维的输入数据，简化为二维x，y平面，竞争学习最佳实践。