资源列表
Algorithm
- 数学算法：高斯塞德尔，牛顿插值，拉格朗日，雅克比。包含各个算法的实现源代码。-Mathematical algorithms: Szczecin del high, Newton interpolation, Lagrange, Jacobi. Contains various implementations of the algorithm source code.
LightTest
- 根据光学设备K10读取屏的信息数据，对该数据进行补色运算及给出最优的解决方法-K10 reads information data of the screen of the optical apparatus, the data complement the color operation and gives the optimal solution
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- 多物理场耦合软件采用有限元方法模拟表面等离子体激元，适合入门学习者-Multi-physics coupling software using the finite element method to simulate the surface plasmon, suitable for entry-learners
casd
- comsol软件采用有限元方法模拟表面等离子体激元-the comsol software using the finite element method simulation of surface plasmon
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- 多物理场耦合软件采用有限元方法模拟表面等离子体激元-comsol multi-physics coupling software using the finite element method simulation of surface plasmon
a
- comsol多物理场耦合软件采用有限元方法模拟表面等离子体激元-comsol multi-physics coupling software using the finite element method simulation of surface plasmon
KMean
- KMEAN C# In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data sp
FB_DataRectification
- 数据校正源码。1、粗大误差识别与剔除功能有多种准则(莱依特、肖维勒、罗蒙诺夫斯基、格拉布斯、狄克逊)，不同准则算法不一样。在一个剔除周期内，对同一变量的n的样本进行粗大误差识别和剔除，样本个数n大于5，小于等于102.2、数据协调功能再粗大误差被剔除的基础上，在满足约束条件下求出无偏最小方差估计解，此解即为数据协调值。-Data correction source. 1 gross error identification and elimination features a variety o
FB_DataMing_kmeans
- k-means数据挖掘算法，基于kmeans聚类算法工艺参数基准值的挖掘-mining data mining of the k-means algorithm, based on the kmeans clustering algorithms process parameters reference value
FB_Str_Split
- 字符串拆分元源码。把全局变量或者字符串变量(split)分解为n个值，这样协助解决1个输出变为多个输出。-The string split yuan source. Global variable or a string variable (split) decomposition of n values, so to help solve an output into multiple outputs.
FB_LeastSquare
- 最小二乘法算法源码C++。实现最小二乘法算法算法计算，内容详实。-The method of least squares algorithm source C++. The method of least squares algorithm algorithm calculated informative.
FB_MultipleRegression
- 多元回归源代码。回归方式：配置为0表示进行多元线性回归；1进行多项式回归；2进行多元二次回归。变量/阶数：回归方式配置为0时表示参与回归的变量数，配置为1时表示回归的阶数；（默认待回归变量不超过6个或拟合阶数不超过6次） -Multiple regression source code. Regression: Configure multiple linear regression polynomial regression 2 multivariate quadratic regre