自组织 Kohonen 映射程序，当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...

OPENCV系列的，TOOLBOX工具，应该挺有用的，大家自己看看吧！-OPENCV series, TOOLBOX tool, it should be quite useless, we all see!

一个关于模式识别问题的很好的例子，可以对数组进行检验，非常好用！-a pattern recognition problem on the very good example of the array can be tested very handy!

用MATLAB编写的svm支持向量机的分类,回归工具箱- MATLAB codes of support vector machine svm classification, regression Toolbox

用Delphi语言编写的遗传算法，内容较多，可以参考-Delphi language prepared by the genetic algorithm, a great deal of content, they can refer to

匈牙利命名法则，关于在编程中变量的命名的一个很好的参考！-Hungary naming rules，a good reference of naming variables in the programming！

从其它网站上下载的用VC++编制的模拟退火算法求解TSP问题的源代码-from other websites downloaded VC simulated annealing algorithm for TSP 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

人工神经网络天气预报方法-ANN weather forecasting method

标准的粒子群优化算法,visual c++.net环境下编写的代码,有助于学习和理解粒子群算法-Standard particle swarm optimization algorithm, visual c++. Net code to prepare an environment to help learning and understanding of particle swarm optimization

神经网络训练程序，用来进行RBF网络的权值训练，利用训练好的权值可以进行自适应滤波！-neural network training procedures used for RBF network weights training. good use of training weights can be adaptive filtering!