SCS

本程序为基于工艺参数优化的改进遗传算法程序-based on the procedures for the optimization of process parameters improved genetic algorithm

二维核密度估计算法.以及最优化计算核宽度。-bivarite kernel estimation

详细介绍了人工智能在故障诊断中的应用 有实例-Details of the artificial intelligence in fault diagnosis are examples of

这是一个遗传算法的代码，用C++写的，运行环境是vs2005.-This is a genetic algorithm code, using C++ Written running environment is vs2005.

曲线的平滑，应用贝塞尔曲线进行平滑，点击要平滑的点即可-With this program you can smooth your data automatically only by selecting the area to be smoothed with 2 clicks. Then INTERP1 is used to smooth. The operation is repeated until you press ENTER.

有关TSP遗传算法的的三个pdf论文。不错的参考-The TSP of the three genetic algorithms pdf papers. A good reference

遗传算法工具包可以解决很多的问题,,非常有用-Genetic algorithm tool kit can be solved many problems, very useful

介绍了根据三菱FX系列PLC编程口通信技术的特点,设计基于VB的PC与PLC机械手远程 控制程序.通过机械手监控系统软件的具体应用,系统地介绍了VB环境下的MSComm通讯控件 ,PLC与上位机的编程口通信协议,系统控制方法设计以及监控软件的实现过程.-Introduced acts according to Mitsubishi FX the series PLC programming mouth communication the characteristic, designs based on VB PC and the PLC manipulator remote control procedure. Through the manipulator supervisory system software s concrete application, introduced systematically VB under the environment MSComm communication controls, PLC and the

采用蚁群算法解决旅行商问题，IDL语言编写，动态现实中间过程。-Using ant colony algorithm to solve traveling salesman problem, IDL language, dynamic realities of the middle of the process.

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