good classification procedure. . . . C language. . . VC development environment.

基于BP算法的贝叶斯网络参数学习， 实现了图形话的节点表示和样本生成， 图形话的结果分析-BP algorithm based on Bayesian network parameter learning, the achievement of the graphics, then the node express and sample generation, if the results of graphical analysis

face recognition test source code

该文件是包含了机器人足球比赛中的整个系统的代码，包括动作，视觉，定位和决策-The document includes a robot soccer competition of the entire system code, including action, vision, positioning and decision-making

改进的遗传算法的三个操作算子，包括选择、交叉和变异。-Improved three arithmetic operator in genetic algorithm including select,crossover and mutuation

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

解非线性规划模型的遗传算法，采用visual c++语言编写，结构清晰，明了易懂，注释完整-Genetic Algorithm for nonlinear programming

美国麻省理工学院出的遗传算法方面的好书.-Massachusetts Institute of Technology in the United States out of aspects of genetic algorithms books.

介绍了神经 网络中的CPN算法的C语言实现.-Introduce a neural network algorithm in C language CPN realize.

基于Matlab的简单遗传算法和简单bp网络的程序实现-based on Matlab simple genetic algorithms and simple bp Network Program

人工智能课程的实验中用C语言环境实现子句归结的算法和反映-experimental artificial intelligence courses using C language environment to achieve phrase attributed to the algorithm and reflect