用BP神经网络逼近函数Z=SIN(X*Y),采用C++编程.

转载：对神经网络中使用最广泛的一种：BP神经网络采用vbmatlab来实现，把训练数据拷入，load的*.m文件中, 文件中部load的*.m为测试数据 save 存盘的文件为测试数据的bp预测值, 该程序可以扩充n个输入,n个输出,很容易-reproduced : the neural network the most widely used one : BP vbmatlab using neural networks to achieve, it is copyed into the training data. m*. load the document, Central to the paper load*. m to save Inventory test data for the paper test data bp predictive value, The procedure can be expanded to import n, n output, it is easy

基于遗传算法的体育彩票拟合与预测，经检验，中奖率高于随机号码。-based on genetic algorithm fitting sports lottery and forecasts, on examination, the winning rate than random numbers.

特别是在题库管理模块中对自动组卷功能常用的算法（包括随机选取法、回溯试探法和遗传算法）进行了比较。对于较流行的验证码技术也给出了具体实现。-particularly in the examination management module to automatically making up the algorithm commonly used functions (including random selection method, Retrospective testing and genetic algorithm) were compared. For more popular authentication code technology has provided a concrete realization.

Libsvm - MATLAB version-Libsvm- MATLAB version

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

我的八数码游戏！！ 学人工智能的编写的-my eight digital game! ! The study prepared by the Artificial Intelligence

神经网络隐节点合成算法，用于神经网络泛化能力的提高，和大家共享！-Hidden node neural network synthesis algorithm for neural network generalization capability, and the U.S. share!

一个遗传算法程序-A genetic algorithm program

遗传算法工具箱及应用，包括了美国那个大学遗传工具箱的应用说明，很好用-Genetic algorithm toolbox and its application, including the United States that the University of the genetic toolbox of application notes, very good use

本书介绍了一些关于机器人的识别技术，值得学习和借鉴，作为基础资料不错-The book introduced a number of robot recognition technology, it is worth to learn from, as a good basis for information