微电网数学模型搭建

说明：  glmark2 测试对象是NVIDIA drive板子。 发现这个跑分软件对于强大的NVIDIA板子而言，没有占用太多资源。(Glmark2 is a popular open source GPU benchmarking tool with OpenGL2 2.0 and OpenGLES 2.0 support, available for Linux and Android platform. It is developed with a goal of easy and effective GPU benchmarking for ARM hardware in embedded systems by the Linaro team. Glmark2 binary packages are available in official Ubuntu repository, but not available in Debian repository, so we have to compile and install latest glmark2 form its git repository.)

说明：  MF-DFA，Kantelhardt et al.(2002)提出的多重分形去趋势波动分析方法(MF-DFA, multifractal detrend fluctuation analysis)

说明：  贝塞尔函数绘图与零点计算，对于传输线理论等计算有帮助(bessel fuction and zero point)

手机三维游戏开发包，提供通用开发模块，减少游戏开发工作量-Three-dimensional mobile game development package, to provide a common development of modules, to reduce the workload of games development

VC++ 弹出和关闭光驱CDROM托盘盒，通过本程序打开电脑光驱的托盘盒，也就是完成出仓和进仓动作，只要是光盘驱动器都是可以的，另外程序还可设置热键、开机启动或最小化到托盘的功能，程序的实现使用了classXP.dll控件。

matlab高斯消去法，帮助解决方程求解问题基础方法(Matlab gaussian elimination)

NILM-Eval是一个MATLAB框架，允许在不同场景中评估非侵入式负载监控算法，以全面了解其性能.NILM-Eval可以轻松评估多个数据集，住户，数据粒度，时间段和特定算法参数的算法。通过将这些参数封装在配置中。NILM评价仪进一步允许用户轻松地重复其他人执行的实验，评估新数据集上的算法，以及微调配置以提高新算法的性能设置(Nilm-eval is a MATLAB framework that allows evaluation of non-invasive load monitoring algorithms in different scenarios to fully understand their performance. Nilm-eval can easily evaluate algorithms for multiple data sets, households, data granularity, time periods and specific algorithm parameters.By encapsulating these parameters in the configuration.NILM evaluator further allows users to easily repeat experiments performed by others, evaluate algorithms on new data sets, and fine-tune configurations to improve performance Settings for new algorithms)

交通仿真相关学术论文，对初学者有一定帮助(Academic papers on traffic simulation are helpful to beginners.)

用ＭＡＸＰＬＵＳ设计的ＣＭＩ程序，好不容易弄到的，-MAXPLUS designed by CMI procedures, easy to get, and

说明：  自适应学习滤波，绘制mse，波形图，估计频率，大学作业，随机信号分析(Adaptive learning filtering, drawing MSE, oscillogram, estimating frequency, college work, random signal analysis)