登录
首页 » Fortran » filon_integration

filon_integration

于 2013-01-03 发布 文件大小:3KB
0 279
下载积分: 1 下载次数: 8

代码说明:

  final积分,一种用于计算积分的快速有效的fortran方法。(final integrate)

文件列表:

filon_integration.F,11310,2012-11-16

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • sw_pres
    根据海水的速度 密度 温度 盐度等计算海洋各处的压力数值(Speed ​ ​ according to the density of seawater temperature and salinity values ​ ​ calculated pressure throughout the ocean)
    2013-10-10 16:36:37下载
    积分:1
  • similarity
    本代码可以用于计算特征向量或者矩阵的相似度。(This code can be used to calculate the similarity of the feature vector or matrix.)
    2012-07-05 11:43:02下载
    积分:1
  • C__4
    The only information passed from difeq to solvde is the matrix of derivatives
    2012-08-23 22:23:00下载
    积分:1
  • PID-algrithm
    对于PID算法给予了通俗易懂的讲解,有利于初学者快速掌握PID的要领(I give the PID algorithm the understandable explanation,which will help beginners to quickly master the PID essentials)
    2012-12-21 15:21:32下载
    积分:1
  • laser18
    光纤激光器速率方程 修改数值后可直接计算(The fiber lasers rate equation)
    2013-05-14 15:46:23下载
    积分:1
  • LSTM_learn-master
    采用LSTM算法用python语言实现的信号时间序列预测,可预测信号的占用度(The LSTM algorithm is used to predict the signal time series in python language)
    2017-10-13 09:45:28下载
    积分:1
  • Fortran-Programs
    Fortran算法程序集,徐士良,第二版,包括源码和pdf。(The Fortran algorithm assemblies, XU Shi-liang, second edition, including source code and pdf.)
    2013-01-17 20:14:40下载
    积分:1
  • LARS-with-LASSO-modification
    带LASSO修正的LARS算法 稀疏表示(LARS with LASSO modification Sparse Representation)
    2020-07-14 10:48:51下载
    积分:1
  • kriging
    包括基本的克里金(Kriging)插值法实现代码,仅实现基本方法部分,不包含扩展克里金方法( kriging uses ordinary kriging to interpolate a variable z measured at locations with the coordinates x and y at unsampled locations xi, yi. The function requires the variable vstruct that contains all necessary information on the variogram. vstruct is the forth output argument of the function variogramfit. This is a rudimentary, but easy to use function to perform a simple kriging interpolation. I call it rudimentary since it always includes ALL observations to estimate values at unsampled locations. This may not be necessary when sample locations are not within the autocorrelation range but would require something like a k nearest neighbor search algorithm or something similar. Thus, the algorithms works best for relatively small numbers of observations (100-500). For larger numbers of observations I recommend the use of GSTAT. Note that kriging fails if there are two or more observa)
    2015-01-08 15:43:50下载
    积分:1
  • Recursive-Identification-of-AUV
    水下机器人在线最小二乘辨识、应急导航策略研究(Recursive Identification of Autonomous Underwater Vehicle for Emergency Navigation)
    2013-03-28 20:40:22下载
    积分:1
  • 696518资源总数
  • 106265会员总数
  • 10今日下载