基本遗传算法的Matlab工具包，在Matlab环境下实现。

BP分类器，用与识别不同模式。-BP classifier, and used to identify different models.

神经网络的开发包，采用c++编写的，使网络资源，大家共享-neural network development kits, prepared by the use of c, network resources and share

Lin-Kernighan聚类算法源代码，下载后可以直接编译执行-Lin-Kernighan clustering algorithm source code, download directly to compile the implementation of

BP神经网络的设计前向型神经网络的实例，基于Matlab环境。-BP neural network design to the examples of neural network, based on the Matlab environment.

最棒的三大计算机视觉、图像图形函数库之一，C语言版本，支持标准C-best of the three major computer vision, image and graphics functions, one C-language version supports standard C

经典的BPN人工神经网络例子源码,可用于函数逼近，预测等方面-classic example of artificial neural network source, function approximation can be used to forecast etc.

人工智能GRAPHSEARCH算法C语言实现-GRAPHSEARCH artificial intelligence algorithm C Language

8王后问题的演示程序,算法封装在类GAQueen，演示程序是界面程序-8 queen problem demo program, the algorithm is packaged in a category GAQueen, demo program is the interface procedures

基于遗传算法的图像模式识别 ,这个是本人收藏的有关遗传算法的源程序-based on genetic algorithm for image pattern recognition, this is my collection of the genetic algorithm source code

落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节,它直接影响着采掘工作面瓦斯涌出量预测的精度,并与煤的变质程度、落煤粒度、原始瓦斯含量、暴露时间等影响因素呈非线性关系。人工神经网络具有表示任意非线性关系和学习的能力,是解决复杂非线性、不确定性和时变性问题的新思想和新方法。基于此,作者提出自适应神经网络的落煤残存瓦斯量预测模型,并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究。结果表明,自适应调整权值的变步长BP神经网络模型预测精度高,收敛速度快 该预测模型的应用可为采掘工作面瓦斯涌出量的动态预测提供可靠的基础数据,为采掘工作面落煤残存瓦斯量的确定提出了一种全新的方法和思路。-charged residual coal gas is to determine the volume of mining gas emission rate forecast an important link, which directly affect mining gas emission rate forecast accuracy, and with coal metamorphism, loading coal particle size, the original gas content, exposure time and other factors nonlinear relationship. Artificial neural networks have expressed arbitrary nonlinear relationships and the ability to solve complex nonlinear, time-varying uncertainty and the new ideas and new approaches. Based on this, the author of adaptive neural network loading coal residual gas production forecast model, and a combination of different loading coal mine gas remnants of the actual test results of research