Vissim资料

12864中文资料，介绍了12864基本的用法-12864 Chinese information on the basic usage of the 12864

数独是一种源自18世纪末瑞士的数学智力拼图游戏。拼图是九宫格（即3格宽×3格高）的正方形状，每一格又细分为一个九宫格。在每一个小九宫格中，分别填上1至9的数字，让整个大九宫格每一列、每一行的数字都不重复。 数独的玩法逻辑简单，数字排列方式千变万化。不少教育者认为数独是锻炼脑筋的好方法。-Sudoku is a kind of Switzerland originated in late 18th century mathematical intelligence jigsaw puzzle. Puzzle is the squares (ie, 3 cells wide × 3 grid H) of square-shaped, each divided into a fine grid squares. Small squares in each of the respective fill in the figures 1-9, so that the whole big squares in each row, each row will not repeat the figures. The logic of playing Sudoku is simple, the arrangement of the ever-changing figures. Many educators think Sudoku is a good way to exercise their brains.

说明：  这是第5版，英文彩色版，字迹清晰，这是从csdn上下载弄过来的。(This is the 5th, writed by English and color paper.)

接收信号，通过服务控制门禁的开启。vc实现websocket服务和stomp协议(Open access control through service control)

实现文本框的控制输入，例如，只输入数字，比较简单，可使用DLL文件(Control input for text box)

gpc预测控制，广义预测控制m程序，实现对滞后系统的控制(Generalized predictive control)

这是LAMMPS中的所有例子，行接触到LAMMPS的新手，不知道在哪下载，我帮你么你列出来了。(This is all the examples in LAMMPS, line access to LAMMPS novice, do not know where to download, I help you you you listed.)

采用能量等值法计算骨架曲线的屈服荷载及位移等(Calculating yield load and displacement of skeleton curve by energy equivalent method)

单相逆变器仿真，MATLABR2016B工程文件，THD小于1%，电压电流双闭环控制，并且加入了负载扰动，控制效果良好(Simulations of single-phase inverters show that the THD of MATLAB R2016B project file is less than 1%. Double closed-loop control of voltage and current is adopted, and load disturbance is added. The control effect is good.)

说明：  在葡萄酒制造业中，对于葡萄酒的分类具有很大意义，因为这涉及到不同种类的葡萄酒的存放以及出售价格，采用神经网络做为分类器可以有效预测相关葡萄酒的种类，从UCI数据库中得到wine数据记录的是在意大利某一地区同一区域上三种不同品种的葡萄酒的化学成分分析，数据里含有178个样本分别属于三个类别(类别标签已给)，每个样本含有13个特征分量(化学成分)，将这178个样本70%做为训练样本，另30%做为测试样本，用训练样本对神经网络分类器进行训练，用得到的模型对测试样本的进行分类标签预测。(In the wine manufacturing industry, classification of wine is of great significance, because it involves the storage and selling price of different kinds of wine. Using neural network as classifier can effectively predict the types of related wine. The wine data recorded from UCI database is the chemical composition of three different kinds of wine in the same region of Italy According to the analysis, 178 samples in the data belong to three categories (the category label has been given). Each sample contains 13 characteristic components (chemical components). 70% of the 178 samples are used as training samples, and 30% are used as test samples. The training samples are used to train the neural network classifier, and the model is used to predict the classification label of the test samples.)