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LevenbergMarquardt
- it is a good programe to use in nonlinear optical aspect-it is a good Nydia to use in nonlinear opt da aspect
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- 主要提供一本比较经典的数据挖掘的数据，由张贤达主编的数据挖掘课本，以此提供一些初学者资料-Mainly provides a more classic data mining of data, edited by ZHANG Xian-da data mining textbooks for beginners in order to provide some information on
getPDF2
- Data assimilation (DA) is a method of combining observation data with model forecast data in order to more accurately predict the state of a system. One of its most common uses is in numerical weather prediction (NWP). In NWP, we have observati
zui-da-liu
- 计算最大流程序，根据顶点，节点的出入度，随机生成网络并计算最大流。-Calculate the maximum flow procedures, randomly generated according to the degree of vertex and node access network and computing the maximum flow.
densityalt
- 利用当前大气层对应的空气密度来计算海拔高度的函数-H = DENSITYALT(rho) returns altitude, H, in the standard atmosphere that corresponds to the provided array of air densities, rho. DENSITYALT is valid for the entire standard atmosphere up through the mesopause (86 km hei
suan-fa-da-quan
- 数学建模各种算法资料及MATLAB源码，包括各种算法分析比较-Various algorithms of mathematical modeling data and MATLAB source code, including a variety of algorithm analysis and comparison
libPLS_1.6
- libPLS: a Library for Partial Least Squares Regression and Discriminant Analysis-This library provides a whole set of easy-to-use functions for building partial least squares (PLS) regression (PLSR) and discriminant analysis (PLS-DA) models as well a
equacao_reta
- algoritmo da Equacao da reta
mochila
- Problema da Mochila (NP-Completo)
CforFFT
- 飒沓，在吃饭打扫打扫。打算打算向常态化的法宝。-Sa Da, at dinner clean sweep. Intends intends to normalization of magic.
Problem_1_2_3
- 2014年全国研究生数学建模大赛E题1-3小题的相关程序-code for 2014 quan guo yan jiu sheng shu xue jian mo da sai
da
- MathCAD,find frequencies
Armadura de Cisalhamento
- Calculo da armadura de cisalhamento segundo a NBR
VaR、ES
- VaR和ES计算的计量经济学方法，VaR的计算得方法以及ES的计算方法(> da=read.table("d-ibm-0110.txt",header=T) > xt=-log(da$return+1) > install.packages("fGarch") > library(fGarch) > m1=garchFit(~garch(1,1),data=xt,trace=F) > m1)