PHPnow的模板4347

说明：  MATLAB/simulink搭建逆变器控制模块，恒压恒频控制方式，dq坐标系，双闭环(MATLAB/simulink builds inverter control module, constant voltage constant frequency control mode, dq coordinate system, double closed loop)

利用Labview实现数组的滑动平均值计算(failed to translate)

说明：  包含P2G的多能互补微网日前经济最优调度。分析了微网可再生能源消纳能力。(Day ahead economic optimal scheduling of multi energy complementary microgrid with p2g. The renewable energy consumption capacity of microgrid is analyzed.)

The functions design of software system is shown in Fig.8. There are some automatic or intelligent algorithms for analyzing and processing the sensed data to be implemented in the system. They are self-adaptive

matlab蒙特卡洛仿真，高斯白噪声中确知信号的检测及其报告(The curve of ROC using Monte-Carlo simulation)

把二进制按制按照DEBUG的形式输出到屏幕或文件。-put by the binary system with DEBUG output in the form of paper or screen.

汽车四自由度系统模型仿真。包括车身垂直振动，俯仰振动，前轴振动，后轴振动对前后车轮的影响。(Simulation of Four - Degree - of - Freedom System Model. Including the vertical vibration of the vehicle body, pitch vibration, front axle vibration, rear axle vibration on the front and rear wheels.)

说明：  jQuery响应式图片无缝切换代码是一款宽屏幻灯片轮播切换特效。(JQuery Responsive Picture Seamless Switching Code is a wide-screen slideshow rotation switching special effect.)

说明：  QT编写周立功CAN通讯测试软件，供大家学习参考(QT write easyarm CAN communication test software, consult for everybody to learn)

说明：  K-means算法是基于划分的思想，因此算法易于理解且实现方法简单易行，但需要人工选择初始的聚类数目即算法是带参数的。类的数目确定往往非常复杂和具有不确定性，因此需要专业的知识和行业经验才能较好的确定。而且因为初始聚类中心的选择是随机的，因此会造成部分初始聚类中心相似或者处于数据边缘，造成算法的迭代次数明显增加，甚至会因为个别数据而造成聚类失败的现象。(K-means algorithm is based on the idea of partitioning, so the algorithm is easy to understand and the implementation method is simple and feasible, but it requires manual selection of the initial number of clusters, that is, the algorithm is with parameters. The number of classes is often very complex and uncertain, so professional knowledge and industry experience are needed to better determine. Moreover, because the selection of initial clustering centers is random, some initial clustering centers will be similar or at the edge of data, resulting in a significant increase in the number of iterations of the algorithm, and even the phenomenon of clustering failure due to individual data.)