搜索资源列表
ChangLHS
- 克里金模型中的改进拉丁超立方取点方法，在实际应用中有较强的意义。-Kriging model to take to improve the Latin Hypercube point method, in practice there is a strong significance.
Cholesky
- 具有相关性的风速序列的拉丁超立方采样方法的例子，包含Cholesky以及排序-Examples of correlation between wind speed sequence of Latin hypercube sampling method, including Cholesky and sorting
Latin-Hypercube-Sampling
- 此源码会产生一个平方空间上随机的领域。样品创建拉丁超立方抽样和空间相关性是基于Cholesky分解算法-This source will generate a random field on a square space. Samples to create a Latin Hypercube Sampling and spatial correlation is based on the Cholesky decomposition
CLMCS
- 潮流计算中拉丁超立方采样的算法，可利用其进行概率潮流计算-Flow calculation Latin hypercube sampling algorithm, can use its probabilistic load flow calculation
LHS
- 拉丁超立方抽样，调用方式如下：S=lhs(m,dist,mu,sigma,lowb,upb) m: a scalar,the number of sample points dist: A row with distribution type flags of basic random variables the value of the flag can be 1 (for uniform distribution, 2(
MATLABCLMCS
- 用拉丁超立方采样方法模拟具有相关性的数组代码-Latin Hypercube Sampling Method cubic correlated array simulation code
LHS-methods
- 拉丁超立方法所有的程序，包括基本采样、相关采样等。-Latin Hypercube method for all programs, including basic sampling, sampling and other relevant.
ilhs
- 附件是改进的拉丁超立方的Matlab源程序-IHS implements the improved distributed hypercube sampling algorithm.
lhs
- 这个程序组是拉丁超立方模拟程序，是高级的monte carlo模拟随机抽样。-This program group is Latin hypercube simulation program, it is the senior monte carlo simulation of random sampling.
NSGA-II
- 拉丁超立方采样matlab程序：在尽可能少的样本点下建立尽可能精确的模型-latin hypercube sample
WT_PV_Load_Scenario
- 针对电力系统中风电和光伏出力以及负荷不确定性问题，该程序通过拉丁超立方抽样和样本削减将其转化为场景分析问题。-For stroke power and photovoltaic power system output and load uncertainty, the program by Latin Hypercube Sampling and sample reduction to convert it into a scene a
LHS
- 拉丁超立方抽样试验设计程序：输入多维变量样本和所需组数，输出基于拉丁超立方抽样方法的实验设计结果-LHS test design program:input the multidimensional variable samples and the number set, output the design of experiment results based on Latin hypercube sampling method
Latin-Hypercube-sample
- 拉丁超立方采样方法是一种科学的试验设计方法，其采样点具有分布均匀，具有代表性等特点。-Latin hypercube sampling method is a scientific method of experimental design, Its sampling points are distribution, representative and so on.
拉丁超立方体抽样
- 完成采样空间的采样，适合于响应面，近似模型之前的采样工作，文件夹中有具体介绍(The sampling space is completed. It is suitable for the response surface and the sampling work before the approximation of the model. The folders are introduced in detail.)
1
- 多参量拉丁超立方抽样，正态分布、均匀分布、参量之间有无相关性(Multi parameter Latin hypercube sampling)
拉丁超立方代码
- 拉丁超立方采样包括还有约束和没有约束的两种。(Latin hypercube sampling includes both constrained and unconstrained sampling.)
lhsdesign
- 生成n维变量的拉丁超立方样本点，直接导出样本点。(Generate the sample points of n-dimensional input vectors.)
不确定性处理方法
- 拉丁超立方抽样，对正态分布进行的抽样，使抽样数据更加均匀(kyewbdhukndfvjrennvgvdgx)
lx_程序
- 1、基于历史风速拟合威布尔分布函数 2、进行拉丁超立方抽样 3、进行后向缩减(1. Fitting Weibull distribution function based on historical wind speed 2. Latin hypercube sampling 3. Backward reduction)
拉丁超立方抽样
- 拉丁超立方，去抽取样本，是一种从多元参数分布中近似随机抽样的方法，属于分层抽样技术，常用于计算机实验或蒙特卡洛积分等。(Latin hypercube sampling)