本代码是一个自适应优化遗传算法的例子，读者可以结合王小平写的书来学习，已经实现了，测试过，可以通过编译计算结果...

我们解决八数码问题,广度优先搜索可能会导致内存不够用,采用启发式搜索,启发函数为f(x)=g(x)+h(x) g(x)为该结点不同于目标结点的个数,h(x)为该结点的深度,选择那f(x)结点最小的那个结点进行扩展, 引入了一个"扩展数组[4]"(因为扩展的结点最多只有4个),该数组保存着某个结点的0点向各个方向的扩展的结点对象,然后对该扩展数组进行分析,利用启发函数在进行递归扩展... -us solve eight digital, BFS may lead to insufficient memory, using heuristic search, heuristic function f (x) = g (x) h (x) g (x) for the target node is different from the number of nodes, h (x) for the nodes of depth, the choice between f (x) nodes that the smallest node expansion. the introduction of an "expanded array [4]" (because the expansion of the nodes at most four), The array maintains a node of 0:00 a.m. to expand in all directions in the target node, and then expanded array analysis, use heuristic function during recursive expansion ...

遗传算法的讲义！- Heredity algorithm printed lecture!

《人工神经元网络》含有实用的网络模型、学习规则和训练方法的一些算法程序，对学习人工智能，模式识别的人有一些帮助！-"artificial neural network" contains practical network model, learning rules and the training methods of some algorithm for the study of artificial intelligence, pattern recognition of some help!

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

LM编程算法，在神经网络中有很大应用之处，神经网络源代码,及BP网络训练界面,其中的L-M算法非常实用 -LM programming algorithm, in a large neural network applications, the neural network source code, and the BP network training interface, in which the LM algorithm is very practical

很好用的一个适用程序，由Visual C＋＋编程，有收藏价值

数据挖掘中频繁项集挖掘算法，改进了apriori算法，性能提高很多-Data Mining frequent itemsets mining algorithm, improved apriori algorithm, improve the performance of many

特征提取技术。这种技术以传统的建模方式为前提，对于产生的模型的几何、拓扑等信息加以分析以提取其特征信息，这种技术一般多采用人工智能及模式识别等方面的知识。-feature extraction technology.

这是一个数据挖掘中的关联规则挖掘的经典算法：Apriori算法的程序-This is the code of Apriori-the classical algorithm used in Association Rules of Data Mining

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