svm forecast thesis on the theory of rough, interested can check out, quite good...

遗传优化神经网络结构，C++源代码-Genetic optimization of neural network architecture, C++ Source code

一个完整BP神经网络源代码，包括数据和说明文档-a complete neural network source code, including data and documentation

RBF实现神经网络预测程序，压缩包，不用解压缩密码！-Realize RBF neural network prediction program, compressed packet, do not extract the password!

我的文件是用VC设计的一个求解人工智能中8数码问题的程序。-my VC document is designed to solve a digital AI 8 issue procedures.

Simulated annealing (SA) for the Symmetric Euclidean TSP

TSP的智能算法，里面包含最大最小蚁群算法，蚂蚁系统，蚁群系统

遗传算法小程序。-GA small programs.

神经网络拟合，试用，本人用于药品浓度拟合之用-neural network fitting trial, I used drugs used concentration Fitting

BP神经网络VC类，此类对BP神经网络进行了封装，整个类是基于动态构建，可以适合于任何采用BP神经网络的模式识别应用。-BP neural network VC categories, such BP neural network to a package, the whole category is based on dynamic construction, and is suitable for use in any BP neural network applications of pattern recognition.

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