人工神经网络神经网络的程序和训练数据 解压缩后可以运行的...

仿真1：首先把网络温度参数T固定在100，按工作规则共进行1000次状态更新,把这1000次状态转移中网络中的各个状态出现的次数Si（i＝1，2，…，16）记录下来 按下式计算各个状态出现的实际频率： Pi=Si/∑i=1,NSi=Si/M 同时按照Bo1tzmann分布计算网络各个状态出现概率的理论值： Q（Ei）=（1/Z）exp（-Ei/T） 仿真2：实施降温方案，重新计算 采用快速降温方案：T（t）= T0/（1+t） T从1000降到0.01，按工作规则更新网络状态 当T=0.01时结束降温，再让T保持在0.01进行1000次状态转移，比较两种概率-a simulation : First of all network parameters temperature T fixed at 100 and, according to the rules for a total of 1000 to update the state, this state of the 1000 network transfer of all states for the number of Si (i = 1, 2, ..., 16) all recorded determined by the formula state-of the actual frequency : Pi = Si/i = 1, NSi = Si/M in accordance with Bo1tzmann distributed computing network of states all probability the theoretical value : Q (Ei) = (1/Z) exp (- Ei/T) Simulation 2 : implementation of cooling, re-using rapid cooling programs : T (t) = T0/(1 t) T dropped to 0.01 from 1000 and, according to the rules updated network state when T = 0.01 at the end of cooling, let T at 0.01 for the 1000 state tran

BOLTZMAN（vc＋＋编写的程序神经网络程序）

java　象棋源程序，人工智能，搜索引擎-java chess source, artificial intelligence, search engines

收集的关于遗传算法的模糊搜索的ppt资料，有兴趣的可以研究一下-Collected on the genetic algorithm ppt fuzzy search information, interested can look at

林火预测元胞自动机的代码，利用它可以对未来的林火情况进行模拟和预测-Forest Fire Cellular Automata prediction code, using it for the future forest fire situation in the modeling and prediction

本算法采用最基本的遗传算法编写，有利于初学者掌握遗传算法的构成。-This algorithm is written by the most fundamental genetic algorithm,benefit the beginner to know the structure of genetic algorithm

非常经典的遗传算法工具包，C语言版本的。包括各种常用算法-very classic genetic algorithm tool kit version of the C language. Including common algorithms

蚁群算法源程序 ，比较实用，有简要说明-蚁群算法源程序 ，比较实用，有简要说明

GA example in Visual Basic 6.5.

pso优化算法的vc++源程序。在vc.net2003下面通过。 建议：看代码之前，请先弄明白pso是怎么回事。然后请对应着来：程序中用Agent代表一只鸟，PSO代表鸟群。阅读源代码，不要顺着看，先看main(),然后按照出现的东西的顺序，一个一个得来。-PSO optimization algorithm vc++ source. In the following vc.net2003 through. Recommendations: look the code before you find out how the PSO story. Then corresponds to: Program with Agent on behalf of a bird, PSO representative of birds. Read the source code, do not look down, look at the main (), then follow the order of things emerging, one by one come.