平台vs2005 模拟固体退火算法实现144个城市的旅行商问题，可设置具体参数...

用遗传算法解决01背包问题，内附测试数据。-Using genetic algorithms to solve knapsack problem 01, enclosing the test data.

用于求解TSP的蚁群算法，C 语言 已经运行过-Basic Ant Colony Algorithm for TSP

完整的3D 模型检索程序，使用C语言编写，可以使学习者从底层研究三维模型的检索框架，同时提供的C语言程序包也可以设计新的三维模型检索算法。-Complete 3D model retrieval, the use of C language, so that students can study three-dimensional model from the bottom of the search framework to provide the C language package can also be three-dimensional model of the design of the new search algorithm.

这是一个将n个样本聚类到m个类别中 将n个样本在m个类里如何分配输出的遗传算法代码。 适应度：sum(i=1_110)sum(j=1_20)【xi-vj】~2-This is a cluster n samples to the m categories will be n samples in the m a class how to allocate the output of the genetic algorithm code. Fitness: sum (i = 1_110) sum (j = 1_20) [xi-vj] ~ 2

用c＋＋写的用于FPGA设计中布图布线的工具源码，有几万行程序，包含文档-using c++ to write for FPGA design the layout of the wiring tools source, there are tens of thousands of procedure, the document contains

一个用VB写的人工智能看病程序源代码，可以参考编写健康咨询类等类似程序-Using VB to write a medical procedure of artificial intelligence source code, can refer to the preparation of health counseling and other similar types of procedures

C++神经网络开发包ANNIE，可以用C++语言开发各种神经网络：如BP，RBF，HOPFIELD等，同时随附件带有基于VC和.NET环境的示例源程序 -C neural network development kits 8am, the C language can be used to develop a variety of neural networks : as BP, RBF, Hopfield, along with the annex and with VC.NET environment example source

用matlab语言编写模拟退火算法，实现0－1被包问题-using Matlab language simulated annealing algorithm to achieve 0-1 by Kit

dos 下运行,蚂蚁找食物,图形演示,动态化显示每一只蚂蚁如何找到事物.-dos run, the ants find food, presentation graphics, dynamic display every ants how to find things.

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 ...