资源列表
energy_forecasting_notebooks
- energy_forecasting_notebooks kaggle competition
VASP52opt
- 维也纳大学Hafner小组开发的进行电子结构计算和量子力学-分子动力学模拟软件包，是目前材料模拟和计算物质科学研究中最流行的软件之一 采用周期性边界条件(或超原胞模型)处理原子、分子、团簇、纳米线(或管)、薄膜、晶体、准晶和无定性材料，以及表面体系和固体(VASP is a complex package for performing ab-initio quantum-mechanical molecular dynamics (MD) simulations using pseudopot
Finite Element Analysis
- 一本有关复合材料的外文书，介绍了一些实例，也有三维正交hashin失效准则的vumat子程序，希望能对你有所帮助。(A foreign language book on composite materials is introduced, some examples, and a VUMAT subroutine with three dimensional orthogonal Hashin failure criteria, which I hope will help you.)
cca
- 对于降维方法中，曲线成分分析（CCA）的实现(For the dimensionality reduction method, the realization of curve component analysis (CCA) is realized.)
matlab q学习 走迷宫
- 在环境中寻找最优路径，自定义出发点和终点，实现智能体与环境交互(Find the optimal path in the environment, customize the starting point and end point, and realize the interaction between the intelligent body and the environment)
MUSIC算法
- 阵列信号处理MUSIC算法MATLAB代码，本代码基于线性一维阵列编写，包括MUSIC、MUM、RootMUSIC、SMUSIC。代码为学习过程中手动编写调试，适合初学者学习使用，代码可直接运行或者移植。(Array signal processing MUSIC algorithm MATLAB code, the code is based on linear one-dimensional array, including MUSIC, MUM, RootMUSIC, SMUSIC. Co
史蒂芬森迭代法
- 数值分析求解程序，适用于工科学生数值分析学习matlab程序(Numerical analysis solution procedure, suitable for engineering students numerical analysis learning matlab program)
Chap04_BinTreeCode
- 数据结构二叉树的实现(binary tree data structure to achieve)
PID控制及其MATLAB仿真（PDF书和程序m文件）
- 先进PID控制及其MATLAB仿真 北京航空航天大学 刘金琨 一书的PDF详细内容及代码 详细介绍PID控制的设计 有文档及相应的matlab代码(Advanced PID control and MATLAB simulation Beihang University PDF Liu Jinkun book details and code Details of PID control design documentation and corresponding matlab cod
IEEE33_3
- 可以利用IEEE33节点模型做配网仿真，该仿真已经在matlab2017b上稳定运行(IEEE33 node model can be used for distribution network simulation.)
crack growth without remeshing
- 这篇文章详细地介绍了扩展有限元的理论，可供初学者学习(this paper presents the details in the theory of extended finite element method, which is helpful)
RandomForset
- 随机森林的训练、随机森林的预测以及结果的展现，全部代码亲测(Random forest training, random forest prediction and result display, all code affinity test.)