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SIMPLER
simple 算法，有详细步骤，几乎步都自带注解，很好理解。(simple algorithm detailed steps to bring their own annotations)
- 2021-01-26 15:28:41下载
- 积分：1
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SVD-QR-method
svd分解，使用qr方法，编译即可运行，需要文件输入(SVD QR method，the program can run successfully, you need a file for input)
- 2020-08-16 10:08:26下载
- 积分：1
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metal0828
金属表面反射模型算法，用于计算不同金属的偏振反射参数。(Metal surface reflectance model algorithm used to calculate the different metal polarized reflectance parameters.)
- 2020-06-29 01:20:01下载
- 积分：1
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Stress-wave-induced-Fracture
计算动力学研究，应力波引起的裂纹扩展问题，供大家学习(Kinetics calculations, crack propagation problems caused by stress wave for everyone to learn)
- 2013-12-28 22:12:46下载
- 积分：1
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perf_plas_J2
说明： 通过MATLAB编程模拟理想弹塑性应力应变曲线(Simulating the stress-strain curve for perfect plasticity by MATLAB coding.)
- 2020-12-10 01:59:19下载
- 积分：1
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4-split2
给定求解区间，用最小二乘法给出函数的零点，并给出迭代次数(Given the solution interval, the zeros of the function are given by the least square method, and the number of iterations is given.)
- 2019-04-10 16:33:03下载
- 积分：1
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线性回归
说明： 能够实现线性回归,里面有一个线性回归的实例(It can realize linear regression. There is an example of linear regression)
- 2020-05-10 09:38:06下载
- 积分：1
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fluentcas
fluent 软件动网格计算的CAS文件和二次开发程序。用来计算一个蜜蜂翅膀摆动时周围流畅的变化。(fluent moving grid computing, software, documents and secondary development of CAS procedures. Used to calculate the wings of a bee when swinging around the smooth changes.)
- 2020-11-03 11:19:53下载
- 积分：1
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pushboard
说明： 用于三维条件下的推板造波法udf,冲程与周期可修改，附带消波udf和cas文件(generating waves with pushboard under 3D condition)
- 2020-12-26 16:49:03下载
- 积分：1
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Conjugate-Gradient-Method
共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method between the method and Newton' s method, it takes only a first derivative information, but to overcome the steepest descent method convergence slow shortcomings, but also to avoid the Newton method needs to be stored Hesse and disadvantages of computing inverse matrix and the conjugate gradient method is not only one of the most useful methods to solve large linear equations, solution of large-scale nonlinear optimization is one of the most effective algorithm. In various optimization algorithm, conjugate gradient method is a very important one. The advantage is that a small amount of memory required, with step convergence, high stability, and does not require any external parameters.)
- 2017-03-14 15:48:15下载
- 积分：1
