模糊技术与神经网络技术选编

人工智能实验§贝叶斯网络的因果推理关系§ 熟悉掌握Bayes定理，学习贝叶斯网络的因果推理-artificial intelligence experiments Bayesian network causal reasoning relations mastery Bayes Theorem, learning Bayesian network causal reasoning

人工神经网络基本模型：BP、ART、Hopfield、SOM-ANN basic model : BP, ART, Hopfield, SOM

MATLAB环境下的遗传算法源程序代码压缩包-MATLAB environment genetic algorithm source code package

一个人工智能方面的小程序,用OPENGL和VC++做到,希望对大家有所启发-artificial intelligence of a small program, OpenGL and VC done, we hope to inspire

AI 人工智能 在C#环境下实现 9宫格 算法-AI

介绍了蚁群算法解决具体问题的优化算法，实践证明效果很好-on the ant colony algorithm for solving specific problems Optimization Practice has proved very effective

用网格优化算法求解tsp问题。。。matlab编写。附有城市坐标用于检验。 -Mesh optimization algorithm used to solve the problem tsp. . . matlab prepared. Coordinate with the city for inspection.

《神经网络模式识别及其实现》源程序-"pattern recognition and neural network to achieve" source

地球模拟器，最经典的人工生命模型,研究人工智能的必看。一般地说，生命都具有新陈代谢、复制和进化的能力。在自然界中，生物是由有限的食物供给和有限的生存空间约束的。在Tierra中，“生物”由一系列能够自我复制的机器代码或程序组成，它在计算机中的复制分别受到计算机的存储空间和CPU时间约束。能有效地占有内存空间和利用CPU时间的生物体，将具有更高的适应度，传递到下一代的机会就越大。 在Tierra中，计算机的RAM（随机访问存储器）中有一块专门的空间，这个空间中放置了一个“祖先有机体”，该祖先有机体根据它的汇编程序代码中的指令开始复制对它的生存是基本的代码。随着有机体的数目的增加，RAM中的空间减少了，因此有机体为了自己的生存空间开始竞争。-Earth Simulator, the most classic of artificial life model, the study of artificial intelligence Watchable. Generally speaking, life is metabolism, reproduction and the ability of evolution. In nature, biomass is limited by the supply of food and limited living space constraints. In Tierra, "biological" to a series of self-replicating machine code or procedure, in which computers were copied by the computer storage space and CPU time constraints. Effective occupy memory space and CPU time using the organisms, will have a higher degree of adaptability, conveying to the next generation the greater the chances. In Tierra, computer RAM (random access memory) is

dv-hop的定位算法，已知网络中几个锚节点就可以计算出网络中其他点的坐标，但这种算法有时由于网络密度的稀疏，可能误差会有一些-dv-hop positioning algorithm, known to the network a few anchor nodes on the network can calculate the coordinates of other points, but this algorithm is sometimes due to the sparse network density may be some errors