MATLAB版遗传算法解TSP问题

JAVA版的蚂蚁算法(Ant Colony Optimization Algorithms) -JAVA version of the ant algorithm (Ant Colony Optimization Algorithms)

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

CMU的自主机器人的软件开发平台, 应用十分广泛, 基本上已经成为一种近似标准, 比较好用, 希望对开发机器人导航算法方面的人有用 -CMU autonomous robot software development platform for a wide range of applications, they have basically become a kind of similar to the standard, more useful, in the hope that the development of robot navigation algorithm useful side

该算法经运行，无任何问题，可用于解决遗传算法求解车辆路线问题-The algorithm by running without any problems, can be used for genetic algorithm to solve Vehicle Routing Problem

ArcObject的空间查询代码，比较简单和初步的供大家一起学习-The spatial query ArcObject code is relatively simple and everyone together for a preliminary study

专家浅谈人工智能，doc文档-expert on artificial intelligence, doc file

HMM用于人脸识别，从OPENCV里提取出来的,非常经典的说-HMM for face recognition, OPENCV extract from the very classical said

产生应用区系统中的噪声可以改变其分布的-Application areas have a system noise can change its distribution

模式识别的一些预处理知识源程序-pattern recognition pretreatment some knowledge source

人工智能模式识别中基于非负矩阵分解生成特征空间的算法-artificial intelligence pattern recognition based on non-negative matrix factorization generation features of the algorithm space