模拟退火算法（解98数学建模灾情巡视问题）

神经网络仿真工具，本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值.-Neural network simulation tool, this program is BP algorithm demo program in which the Levenberg-Marquardt algorithm has practical value.

这是一个简单的GA代码，为新手用户提供参考

黑白棋子的算法程序实现详细步骤及实现过程-reversi son algorithm program and detailed steps for achieving

包含了许多的最优化算法，有牛顿法，单纯形法等，都已运行通过了-Contains a number of optimization algorithms, there is Newton" s method, simplex method, etc., have to run through the

经典的BNP神经网络例子-classic example BNP neural network

8。《遗传算法及其应用》，陈国良等编着 人民邮电出版社 2001年第一版 本书系统全面地介绍了遗传算法的基本原理、设计方法及其并行实现，以及它在组合优化、机器学习、图像处理、过程控制、进化神经网络、模糊模式识别和人工生命等方面的应用。 本书可作为高等院校计算机、无线电电子学、自动控制、生物医学工程等有关专业高年级学生或研究生的教材和参考书，也可供从事人工智能、信息处理研究和应用的科技人员学习参考。-8. "Genetic algorithm and its application," Chen Guoliang edited and published with the People"s Post and in 2001 the first book version of the full introduction of the genetic algorithm basic tenets , design methods and parallel implementation, and its portfolio optimization, machine learning, image processing, process control, evolutionary neural networks, Fuzzy Pattern Recognition and Artificial Life, and so on the application. The book can be used as institutions of higher learning computers, radio electronics, automatic control, biomedical engineering, and other professional grade students or graduate teaching and reference materials, are also available in artificial intelligence, information processing and application of information technology to study.

《游戏编程中的人工智能技术》一书中10，11章源代码- Game programming in artificial intelligence technology, one source book, Chapter 10,11

遗传算法求解优化问题，简明教程加示例- The heredity algorithm solution optimization question, the concise course adds the demonstration

PCA codes for face detection

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 ...