-
NEH_ForTFT
排序问题的NEH算法,用于解决最小总完工时间的无等待流水调度问题,是最有名的启发式算法(NEH algorithm is the best algorithm
for serching the minimum total flow time of no wait flow-shop porblem )
- 2020-08-25 16:38:16下载
- 积分:1
-
jsffbg
计算方法实验报告:
编程环境:MATLAB7.0
牛顿K次插值多项式的程序实现
龙贝格求积公式的程序实现
高斯列主元消去法的程序实现.(report : Programming Environment : Newton MATLAB7 K polynomial interpolation procedures to achieve Romberg of Quadrature program Gaussian out PCA Elimination of the program.)
- 2006-06-08 12:29:22下载
- 积分:1
-
geatbsrc_v380p
这是解决优化问题的遗传算法压缩包,实用性强,可以应用于不同的专业领域。(This is a genetic algorithm to solve optimization problems compressed, practical, can be applied to different areas of expertise.)
- 2013-10-20 19:18:37下载
- 积分:1
-
interpolation-code
数学建模 插值matlab 代码 第十三讲(Mathematical modeling the interpolation code
)
- 2012-10-14 16:07:54下载
- 积分:1
-
dh366
有信道编码,调制,信道估计等,包括主成分分析、因子分析、贝叶斯分析,包括最小二乘法、SVM、神经网络、1_k近邻法。( Channel coding, modulation, channel estimation, Including principal component analysis, factor analysis, Bayesian analysis, Including the least squares method, the SVM, neural networks, 1 _k neighbor method.)
- 2017-04-04 17:53:45下载
- 积分:1
-
圆柱扰流
Matlab 实现格子玻尔兹曼方法,可以直接运行,很适合初学者(Lattice Boltzmann method implemented by Matlab)
- 2017-10-26 15:33:37下载
- 积分:1
-
MOGWO
说明: 完美运行的多目标灰狼算法,运行文件MOGWO即可进行试验。
可以借助学习灰狼算法,多目标优化。(The perfect multi-objective Gray Wolf algorithm can be tested by running the file mogwo.
With the help of Grey Wolf algorithm, multi-objective optimization can be achieved.)
- 2021-01-21 16:18:46下载
- 积分:1
-
roboFIS
matlab code for robot command using fuzzy analysis
- 2013-10-09 21:50:25下载
- 积分:1
-
auction_match
本人验证的非对称分配拍卖算法程序,非常稳健,可用于求解最优化问题(an asymmetric auction algorithm for max/min problem)
- 2015-10-01 15:28:43下载
- 积分:1
-
qrtrannnn
功能:对矩阵A的左上角的m阶对角块作QR变换:先用Givens变换作QR分解A=QR,
再作相似变换A:=Q AQ=RQ.
输入: n阶HessenbergA,其中A(m+1,m)=0,m>2.
输出: 变换后的Hessenberg形矩阵A.
2 用基本QR算法求实方阵的全部特征值.(Function: the upper left corner of the matrix A, diagonal blocks of order m to QR transformation: first, to make QR decomposition using Givens transformations A = QR, re-similarity transformation A: = Q' AQ = RQ. Input: n-order HessenbergA, where A (m+1, m) = 0, m> 2. Output: transformed Hessenberg form matrix A. 2 matrix with the basic QR algorithm for all the characteristics of the value of truth-seeking.)
- 2009-12-16 16:36:45下载
- 积分:1