代码搜索：Optimization
找到约 10,000 项符合「Optimization」的源代码
代码结果 10,000
www.eeworm.com/read/380715/9134006
m unc_n2_branin.m
function [f]=unc_n2_branin(x)
%reference:
%note that you can get the formulation of unc_n2_branin from some
%aritcles,such as
%(1)X Liu 'Finding Global Minima with a Computable Filled Function',
www.eeworm.com/read/380715/9134007
m unc_n2_camel3.m
function [fval]=unc_n2_camel3(x)
%reference:
%note that you can get the formulation of unc_n2_camel3 from some
%aritcles,such as
%(1)LS Zhang, CK Ng, D Li, WW Tian 'A New Filled Function Method f
www.eeworm.com/read/380715/9134023
m unc_n2_sin.m
function [fval]=unc_n2_sin(x)
%reference:
%note that you can get the formulation of unc_n2_sin from some
%aritcles,such as
%(1)LS Zhang, CK Ng, D Li, WW Tian 'A New Filled Function Method for Glo
www.eeworm.com/read/380715/9134055
m unc_n2_sin1.m
function [fval]=unc_n2_sin1(x)
%reference:
%note that you can get the formulation of unc_n2_sin1 from some
%aritcles,such as
%(1)LN de Castro, FJ Von Zuben 'Learning and optimization using the clo
www.eeworm.com/read/380715/9134125
m unc_n1_sin.m
function [fval]=unc_n1_sin(x)
%reference:
%note that you can get the formulation of unc_n1_sin from some
%aritcles,such as
%(1)LN de Castro, FJ Von Zuben 'Learning and optimization using the clona
www.eeworm.com/read/380715/9134128
m unc_n2_treccani.m
function [f]=unc_n2_treccani(x)
%reference:
%note that you can get the formulation of unc_n2_treccani from some
%aritcles,such as
%(1)LS Zhang, CK Ng, D Li, WW Tian 'A New Filled Function Method
www.eeworm.com/read/180274/9313895
dox lemga.dox
/** @mainpage
* @section intro Introduction
* LEMGA stands for ``Learning Models and Generic Algorithms.''
*
* It was rewritten from an old implementation and is still under
* development and
www.eeworm.com/read/375212/9369014
m grad1.m
function df=grad(x)
%GRAD1 Calcualtes Jocobian of objective function for training NNPLS
% Routine to calculate the Jacobian of fun1 for optimization with leastsq.
% grad1 here is different from gra
www.eeworm.com/read/176114/9515927
m pso.m
%主函数源程序（pso.m）
%基本粒子群优化算法（Particle Swarm Optimization）
c1=2; %学习因子1
c2=2; %学习因子2
w=0.9; %惯性权重
MaxDT=2000; %最大迭代次数
D=5; %搜索空间
www.eeworm.com/read/362500/9996143
m inner1.m
function [x,f0]=inner1(n,b,t,u,plots)
%INNER1 Fits one dimensional nonlinear inner relationsip to score data
% Routine to fit a one dimensional nonlinear inner relationship to score data.
% Inp