演化程序――遗传算法和数据编码的结合 具体介绍了遗传算法的应用...

模式识别中的感知机算法实现，在matlab下实现-Pattern Recognition Perceptron algorithm in matlab to achieve

介绍人工智能语言Prolog的书籍-introduced artificial intelligence language books Prolog

A星算法+强启发函数解八数码问题，自带判断是否有解-A Star Algorithm+ strong heuristic function solution of 8 digital issues, bring their own to determine whether the broken

用Fast BP实现复杂的函数逼近,对初学者有一定的帮助,是在BP的基础上增加了R.-Fast BP achieved with a complex function approximation, there is some help for beginners, is based on the BP increase in R.

经典的人工智能问题 - iris数据分析问题。通过设计三层bp神经网络对花朵数据进行分类识别，并达到了很好的效果。-classic AI problem- iris data analysis problems. Three-bp through the design of neural networks classify data flower identification, and to achieve good results.

包括883分酒问题，图的遍历等人工智能基本算法-Including 883 hours of liquor problem, artificial intelligence, such as graph traversal algorithm

这是一个神经网络开发包。目录ann下是专门针对神经网络的代码，外部目录是一些公用的代码，与神经网络无关，但是神经网络的代码用到了它们。 ann目录下有一个目录demo，里面存放了一些示例程序，请参照它们进行编程。 ann/prj/vs7下是编译整个库的Visual Stdudio 2003工程文件-This a neural network development kit. Ann directory under specific neural network code, external directory is some common code, has nothing to do with the neural network, but neural networks use of their code. Ann directory is a directory demo, stored inside a sample program, please refer to their program. Ann/prj/vs7 under compiler for the entire 2003 Visual Stdudio engineering documents

BP网络解决异或问题的实例，有初始值和最终结果的显示。本网络结构为三层BP网络，各层神经元个数可变，更改相关#define即可。（注释较详细，主函数中调用的函数和矩阵类都定义在文件function.h中）-BP network to solve XOR problem instance, there are initial values and final results are displayed. The BP network structure for the three-tier network of neurons in the number of floors variable, change the relevant# Define you. (Note more detailed, the main function calls the function and matrices are defined in the document in function.h)

SCS-C is another port to C of Goldberg s Simple Classifier System, with a few extensions.-SCS-C is another port to C of Goldberg s Simple Classifier System, with a few extensions.

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.