kalyp是人工生命和神经网络方面架构最全的代码，对于进行仿真代码实现很有参考价值。...

该软件通过BP神经网络学习机制，能够对屏幕上的数字进行识别。-the software through BP neural network learning mechanism, to right on the screen digital identification.

人工智能方面一个专家系统的简单例子-artificial intelligence expert system for a simple example

用元胞自动机实现单色10000个空间位置的细菌分裂试验的算法C语言代码-Using Cellular Automata 10,000 monochrome realize spatial location of bacteria to split the test algorithm C language code

利用c语言实现人工智能神经网络的bam算法-Using c language bam neural network artificial intelligence algorithms

用BP神经网络实现曲线的模拟-BP neural network simulation curve

MATLAB神经网络工具箱ＢＰ算法的比较，比较它们的训练时间长短以所达到的效果-MATLAB neural network toolbox BP algorithm compares the length of their training time in order to achieve the effect of the so

对于具有一定规模的TSP问题的求解，至今没有较完善的求解办法。本程序是用遗传算法来求解TSP问题。-for a certain size of the TSP solution and there has been no better way to solve. This procedure is used genetic algorithms to TSP.

此为蚂蚁算法求解TSP的源代码，希望对大家有所帮助-This is the ant algorithm to solve TSP source code, and they hope to help everyone

这是我自己编的从数据中自动提取模糊规则的程序,这个文件中包括了一个主程序和几个函数,能够自动提起模糊规则、合并优化模糊规则。-This is my own series of the data from the automatic extraction of fuzzy rules procedures, the document includes a main program and several function, can automatically initiate fuzzy rules, merging optimization fuzzy rules.

GENNET是一个通过遗传算法优化权重的16个神经元的全连接神经网络。训练目的是使网络在一定假设的激励下，随时间产生同目标函数同样的响应，即:可以把此网络制作为一个任意波形的信号发生器。 程序分3个示例说明遗传算法进化过程中网络输出的变化趋势。可以看出网络输出（蓝色曲线）随着时间变化逐渐逼近目标函数（红色曲线）。此程序不仅可以学习遗传算法，也可以用于研究全连接网络的直观示例。-GENNET is a genetic algorithm to optimize the weights by the 16 neurons fully connected neural networks. Training purposes is to enable network inspired by certain assumptions, over time, produce the same response with the objective function, namely: the network can be produced as an arbitrary waveform signal generator. Procedure, three examples illustrate the evolution of genetic algorithms in the network output trends. We can see that the network output (blue curve) changes over time, gradually approaching the objective function (red curve). This program can not only learn from the genetic algorithm can also be used to study visual example of a fully connected network.