资源列表
examples
- 采用20结点六面体等参元计算端部受横向力的悬臂梁，内含输入参数(A 20-node hexahedron isoparametric element is used to calculate the cantilever beam subjected to lateral force at the end. The input parameters are included.)
exam7_2
- 采用薄板三角形单元计算斜板的弯曲，内含斜板尺寸示意图(The bending of inclined plate is calculated by using thin plate triangular element, and the sketch of inclined plate size is included.)
arma
- 用于风功率预测的ARMA代码，可在matlab上运行，包含风电数据。(ARMA code for wind power prediction can be run on matlab, including wind power data)
ARIMA预测
- ARIMA整合移动平均自回归模型，时间序列预测分析方法之一，可用于股价预测。(ARIMA integrates moving average autoregressive model and time series forecasting analysis method, which can be used for stock price forecasting.)
Simulink汽车仿真实例(20180614152229)
- 汽车仿真实例包括发动机离合器等的SIMULINK仿真10学时(Automobile simulation examples include SIMULINK simulation 10 hours of engine clutch, etc.)
example
- 此模型是基于MATLAB-simulink，用boucwen滞回模型分析单自由度体系的振动反应(This model is based on MATLAB-simulink. The boucwen hysteresis model is used to analyze the vibration response of a single-degree-of-freedom system.)
boucwen_2story_
- 此boucwen滞回模型建立在matlab-simulink仿真基础上(The boucwen hysteresis model is based on matlab-simulink simulation)
parameters_2_story(1)
- 此代码是2个自由度的bouc-wen模型代码，如有漏洞，敬请指出(This code is a Bouc-Wen model code with 2 degrees of freedom. If there is a loophole, please point out)
非线性动力学-分岔图-混沌-程序
- 上海交通大学非线性动力系统的分岔图绘制实例，非常简单好用。(The example of drawing bifurcation diagram of non-linear dynamic system in Shanghai Jiaotong University is very simple and easy to use.)
smoke
- 用于识别火灾烟雾 , 火灾先有烟雾后有火, 监测烟雾比监测明火重要的多. 本数据集含有图片400多张, 包括标注好的txt文件, 可以直接用于yolo训练.(Used to identify fire smoke, fire smoke first and then fire, monitoring smoke is more important than monitoring open fire. This data set contains more than 400 pictures,
样条插值
- 样条插值的研究背景，样条函数的力学意义，三次样条插值多项式的构造，一般的插值问题(Research background of spline interpolation, mechanical meaning of spline function, construction of cubic spline interpolation polynomials, general interpolation problems)
EEGNet-master
- EEGNet的python实现，复现论文：A Compact Convolutional Network for EEG-based Brain-Computer Interfaces(Python implementation of EEGNet)