%%%??
%%%??案例：Y?=?G（Xt）?=?-30?+?x1^2*x2?-?5*x1*t?+?（?x2?+?1）*e^（t^2）
%%%??x1~N（3.50.3^2）??x2~N（3.5?0.3^2）??t:[00.5]
%%%??
%%%??本程序可以無(wú)償使用，但不對(duì)實(shí)際結(jié)果做保證。
%%%??2020.08
clear;
clc;

addpath（‘dace‘）;
addpath（‘test_problem‘）;
addpath（‘EOLE‘）;

m=1;????????????????%?算法重復(fù)運(yùn)行次數(shù)，用于多次求平均
mm?=?10;????????????%?平均的次數(shù)
%?pf_every?=?0;???????%?單次運(yùn)行的失效概率
LF_mun?=?0;???????????%?LF?經(jīng)過(guò)很多次迭代，依舊不能大于2的次數(shù)
negt_0?=?0;?
while?（m<=mm）
????clearvars?-except?m?mm?pf_every?N_train_point?qq?pp??Covpf1?LF_mun?negt_0
????
????q_evaluation?=?1;
????
????fun_name?=?‘ANovelSingleLoop4_3‘;?%?ANovelSingleLoop4_1?;?Testhuzhen4_1
????Z=0;???????????????????????????????????%失效的閥值
????%?pf_true?=?0.084861;??????????????????
??????????????????????????%?4-1函數(shù)實(shí)際失效概率初始樣本為5，Nt0=100
??????????????????????????%?Nt1=5T_Nmcs?=?Nt1*50;Nmcs_0?=?1e4;
????%?pf_true?=?0.0569;
????%?pf_true?=?0.1182;
??????????????????????????%?4-2函數(shù)實(shí)際失效概率，theta_e?=?0.9?或?0.85
????pf_true?=?1.24e-4;
??????????????????????????%?4-3函數(shù)實(shí)際失效概率，動(dòng)態(tài)隨機(jī)過(guò)程的簡(jiǎn)支梁
????%?pf_true?=?1.09e-4;?????????????????????
??????????????????????????%?Testhuzhen4_1函數(shù)實(shí)際失效概率

????num_initial_sample?=?10;????????????????%?初始訓(xùn)練樣本數(shù)
????Nt0?=?5;?????????????????????????????%?初始樣本點(diǎn)離散時(shí)間的采樣數(shù)，求極值
????Nt1?=?5;???????????????????????????????%?求新增樣本點(diǎn)的極限值對(duì)應(yīng)的時(shí)間離散
????T_Nmcs?=?Nt1*50;???????????????????????%?T_Nmcs為單個(gè)新增樣本點(diǎn)，通過(guò)kriging_model_2求解時(shí)間
????Nmcs_0?=?1e5;
????Nmcs?=?Nmcs_0;
????EI_epsilon?=?1e-7;????%?EI_epsilon的取值范圍很難確定多少合適
????%?LF_epsilon??=??1e-4?;????%?學(xué)習(xí)函數(shù)的收斂準(zhǔn)則
????%?U_epsilon?=?2;
????Covpf_epsilon?=?0.05;????%?0.05?或?0.02
????
????%?---得到輸入?yún)?shù)變量，num_vari隨機(jī)變量數(shù)，mu均值，sigma方差，t時(shí)間）---
????[num_vari1musigmat]?=?Test_Function（fun_name）;
????num_vari2?=?num_vari1+1;

????for?i1=1:num_vari1??????????%?生成樣本，采用拉丁超立方抽樣法
????????sample_xs（:i1）=?lhsnorm（mu（:i1）sigma（:i1）num_initial_sample）;
????end

????%?sample_Ts=t（11）+（t（21）-t（11））*lhsdesign（Nt11‘criterion‘‘maximin‘‘iterations‘1000）;
????
????%?EGO?求極值響應(yīng)與時(shí)間
????for?i?=?1:num_initial_sample????????
????????
????????sample_Ts?=?t（11）+（t（21）-t（11））*rand（Nt01）;?????%?生成隨機(jī)離散時(shí)間
????????xs?=?ones（Nt01）*sample_xs（i:）;
????????Xs?=?[xssample_Ts];
????????Ys?=?feval（fun_nameXs）;
????????p（i）?=?1;
????????while?（?p（i）?==?1??||??best_EI?>=?EI_epsilon?）
????????????
????????????kriging_model_1?=?dacefit（sample_TsYs‘regpoly0‘‘corrgauss‘1*ones（1num_vari2）0.001*ones（1num_vari2）1000*ones（1num_vari2））;

????????????Mcs_Ts?=?t（11）+（t（21）-t（11））*rand（T_Nmcs1）;?????%?生成隨機(jī)離散時(shí)間
????????????
????????????[Mcs_Ymse_t]?=?predictor（Mcs_Tskriging_model_1）;
????????????cc=?0:0.001:1;
????????????sample_Ts_NNN?=?t（11）+（t（21）-t（11））*cc;
????????????
????????????sample_Ts_NNN?=?sample_Ts_NNN‘;
????????????Xs_NNN?=?[ones（10011）*sample_xs（i:）sample_Ts_NNN];
????????????sample_Ys_NNN?=?feval（fun_nameXs_NNN）;
????????????
????????????hold?on;
????????????plot（sample_TsYs‘r^‘）;???%?Kriging的幾個(gè)訓(xùn)練樣本點(diǎn)
????????????plot（M

?屬性????????????大小?????日期????時(shí)間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2020-09-17?11:57??Kriging代理模型EGO算法\
?????文件?????????378??2019-05-06?11:02??Kriging代理模型EGO算法\.gitattributes
?????文件?????????649??2019-05-06?11:02??Kriging代理模型EGO算法\.gitignore
?????目錄???????????0??2020-09-17?11:57??Kriging代理模型EGO算法\EOLE\
?????文件?????????405??2020-09-12?16:56??Kriging代理模型EGO算法\EOLE\EOLE_Gp.m
?????文件?????????277??2020-09-12?16:52??Kriging代理模型EGO算法\EOLE\EOLE_Gp_rou.m
?????文件?????????819??2020-09-12?16:46??Kriging代理模型EGO算法\EOLE\yt_test1.m
?????文件?????????536??2020-09-12?16:18??Kriging代理模型EGO算法\EOLE\yt_test2.m
?????文件??????????56??2019-05-06?11:02??Kriging代理模型EGO算法\Gaussian_CDF.m
?????文件??????????60??2019-05-06?11:02??Kriging代理模型EGO算法\Gaussian_PDF.m
?????文件?????????912??2019-05-06?11:02??Kriging代理模型EGO算法\Infill_Standard_EI.m
?????目錄???????????0??2020-09-17?11:57??Kriging代理模型EGO算法\KL\
?????文件????????2958??2019-05-06?11:02??Kriging代理模型EGO算法\KL\KL.asv
?????文件????????2777??2019-05-06?11:02??Kriging代理模型EGO算法\KL\KL.m
?????文件????????2014??2019-05-06?11:02??Kriging代理模型EGO算法\KL\KL_fredholm_nystrom.m
?????文件????????4969??2019-05-06?11:02??Kriging代理模型EGO算法\KL\examples_1D.asv
?????文件????????4969??2019-05-06?11:02??Kriging代理模型EGO算法\KL\examples_1D.m
?????文件????????3382??2019-05-06?11:02??Kriging代理模型EGO算法\KL\examples_2.m
?????文件????????5173??2019-05-06?11:02??Kriging代理模型EGO算法\KL\gauss_quad.m
?????文件?????????373??2019-05-06?11:02??Kriging代理模型EGO算法\LF_U.m
?????文件????????2453??2019-05-06?11:02??Kriging代理模型EGO算法\LHS.m
?????目錄???????????0??2020-09-17?11:57??Kriging代理模型EGO算法\dace\
?????文件????????1785??2019-05-06?11:02??Kriging代理模型EGO算法\dace\Copy_of_predictor.m
?????文件?????????407??2019-05-06?11:02??Kriging代理模型EGO算法\dace\Untitled.m
?????文件????????1207??2019-05-06?11:02??Kriging代理模型EGO算法\dace\corrcubic.m
?????文件????????1039??2019-05-06?11:02??Kriging代理模型EGO算法\dace\correxp.m
?????文件????????1176??2019-05-06?11:02??Kriging代理模型EGO算法\dace\correxpg.m
?????文件?????????946??2019-05-06?11:02??Kriging代理模型EGO算法\dace\corrgauss.m
?????文件????????1091??2019-05-06?11:02??Kriging代理模型EGO算法\dace\corrlin.m
?????文件????????1227??2019-05-06?11:02??Kriging代理模型EGO算法\dace\corrspherical.m
?????文件????????1868??2019-05-06?11:02??Kriging代理模型EGO算法\dace\corrspline.m
............此處省略18個(gè)文件信息