这是蚁群算法的一个模拟的软件,可以看到整个蚁群觅食的具体过程,对算法的理解很有帮助....

用神经网络算法求解tsp问题。。。matlab编写。附有城市坐标用于检验。 -Using neural network algorithm for solving the problem tsp. . . matlab prepared. Coordinate with the city for inspection.

关于apriori算法的一个小程序，用于数据挖掘关联规则，呵呵．-apriori algorithm on a small procedures for data mining association rules, Ha ha.

用GAlib库实现的解决0/1背包问题的遗传算法程序源代码。- Solution 0/1 knapsack question heredity algorithm procedure source code realizes which with the GAlib storehouse.

关于语音情感识别的一篇论文，里面描述了人工神经网络的方面-Speech Emotion Recognition on a paper, which describes aspects of artificial neural network

开发环境:Matlab 简要说明:自组织特征映射模型(Self-Organizing feature Map)，认为一个神经网络接受外界输入模式时，将会分为不同的区域，各区域对输入模式具有不同的响应特征，同时这一过程是自动完成的。各神经元的连接权值具有一定的分布。最邻近的神经元互相刺激，而较远的神经元则相互抑制，更远一些的则具有较弱的刺激作用。自组织特征映射法是一种无教师的聚类方法。-development environment : Matlab Brief Description : Self-Organizing Map model (Self-Organizing Map feature), a neural network that external input mode, will be divided into different regions, the regional input to the model with different response characteristics and the process is automatic End %. The neurons connect with the right to a certain value of the distribution. Most neighboring neurons stimulate each other, distant neurons were mutual inhibition, the vision has a weaker stimulus. Self-organizing feature mapping method is a non-teachers clustering method.

该程序是基于BP网络的PID控制系统。系统由两部分构成：经典的PID控制器和神经网络。-that the procedure was based on BP network PID control system. System consists of two parts : the classic PID controller and neural networks.

遗传算法和神经网络的结合应用，通过Visual C++环境来实现该功能，使计算能力更强-Genetic algorithms and neural networks combination of applications, through the Visual C++ environment to achieve this feature, so that more computing power

libsvm在matlab中的应用。把libsvm嵌入matlab中调用。-libsvm in matlab application. Embedded matlab to call libsvm.

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

另一个足球机器人程序，有非常好的参考价值-Another robot football program, there are very good reference value