支持向量机程序(2)Text Windows Svm

自已写的Adaboost使用Haalike feature，去Detection-Adaboost use their own written Haalike feature, to Detection

微软的基于HMM的人脸识别原代码, 非常经典的说-Microsoft HMM-based Face Recognition source, said the very classic

模拟退火算法实验，使用MATLAB实现。-The simulated annealing algorithm, using MATLAB experiment.

基于小波神经网络算法的流域日径流预报模型，该例程为结合型小波神经网络的例子-based on wavelet neural network algorithm watershed day runoff forecasting model, the combination of routines for wavelet neural network examples

优化算法算例,其中有优化算法的相关例子，供学习使用-Optimization examples, including relevant examples of optimization algorithm for learning to use

c语言实现人工智能art1网络的算法实现 -c language art1 network artificial intelligence algorithms

基于神经网络的字母识别系统 -Letters based on neural network recognition system

这是一个HOPFIELD神经网络程序，里面有MAKEFILE，方便读者运行-HOPFILED This is a neural network program, which has MAKEFILE easy operation

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

遗传算法优化神经网络结构和链接权，采用浮点数编码-Genetic algorithm neural network structure and link the right to use floating-point encoding