yingshiziyuan

k在VC中对话框程序中实现切分窗口的控件类,不错的源码(K in VC dialog box procedure of segmentation window in the control class, a good source)

T-SNE高维数据降维特征提取，用于python3(T-SNE demensinal,python)

用于将txt格式数据，转换为.dat格式的数据，便于CASS处理。(Txt format for the data is converted to. Dat format, easy CASS processing.)

AgoodC++programlistsahighreferencevalue()

功能极为强大的可视化汉化集成工具，可直接浏览、修改软件资源，包括菜单、对话框、字符串表等； 另外，还具备有 W32DASM 软件的反编译能力和PEditor 软件的 PE 文件头编辑功能，可以更容易的分析源代码，修复损坏了的资源，可以处理 PE 格式的文件如：EXE、DLL、DRV、BPL、DPL、SYS、CPL、OCX、SCR 等 32 位可执行程序。该软件支持插件，你可以通过增加插件加强该软件的功能， 原公司在该工具中捆绑了 UPX 的脱壳插件、扫描器和反汇编器.，非常好用。(The powerful visualized Chinese integration tool can browse and modify software resources directly, including menus, dialog boxes, string tables, etc. In addition, it also has the decompilation ability of W32DASM software and the PE file header editing function of PEditor software, which makes it easier to analyze source code and repair damaged resources. It can handle 32-bit executable programs in PE format such as EXE, DLL, DRV, BPL, DPL, SYS, CPL, OCX, SCR, etc. The software supports plug-ins, you can strengthen the function of the software by adding plug-ins. The original company bundled UPX shell plug-ins, scanners and disassemblers in the tool. It is very useful.)

linux下的USB和网络驱动程序代码，可以参考。-under linux USB and network driver code for reference.

hslogic算法仿真，基于matlab的OFMD注水法仿真与分析。(Hslogic algorithm simulation, matlab based OFMD water injection method simulation and analysis.)

String类，分享一下。可以实现==, >, <, [], <<, Trim, Reverse, Find, upper, lower等功能(String脌脿 拢 卢 脰脧铆脪 禄脧脗 隆 拢 驴 脡脪脭脢渭脧脰 ==,)

说明：  针对使用传统分类器预测配变重过载会因为重过载样本率较低而带来的总正确率很高，重过载预测正确率却很低这一问题，将重抽样与随机森林理论引入分类模型中，构建重抽样-随机森林分类器对配变重过载进行预测。结果表明，新方法在预测配变日重过载类型、重过载开始与结束时间、重过载严重程度方面有较高的准确率。(For the problem of using the traditional classifier to predict the distribution of heavy overload, the total correct rate is high because of the low overload sample rate, and the accuracy of the heavy overload prediction is very low. The resampling and random forest theory are introduced into the classification model. In the construction, the re-sampling-random forest classifier is used to predict the heavy-duty overload. The results show that the new method has higher accuracy in predicting the type of daily variable overload, the start and end time of heavy overload, and the severity of heavy overload.)

graphics porocess source file