%%?文件說明
%?main.m???:?主文件，進行預測，將生成的網絡保存到?‘nets.mat‘中
%?main_back.m?:?使用‘nets.mat‘重現結果
%?nets.mat?:?保存?3?*?48?個grnn網絡，用于結果重現
%?QLD1.csv?:?原始數據（用的什么時候的數據你點開看一下就明白了）
%?QLD1.mat?:?導成matlab格式的數據
%?optimizeGrnn.m?:?使用模擬退火優化grnn的spread參數
%?adaboost?:?組合算法?輸出結果的第一個數是組合后的mape

%%?原理
%?一周共使用48個神經網絡
%?輸入前一個周7個相同時間點的數據?得到?本周7個相同時間點的數據

%%?注意
%?老婆大人你只需要注意我加?‘%%‘?標注的代碼
%?不用執行本文件，運行‘main_back.m‘即可看到結果
%?net1MeanMape?=
%????0.0165????????<-?grnn1
%?net2MeanMape?=
%????0.0168????????<-?grnn2
%?net3MeanMape?=
%????0.0168????????<-?grnn3
%?combineMeanMapes?=
%????0.0157????????<-?adaboost

clc;
close;
clear;

testWeekNum??=?1;
%%?訓練數據周數
trainWeekNum?=?228;

load?QLD1;
QLD1?=?reshape（QLD1?48?length（QLD1）/48）;

testWeekInd??=?1;
trainWeekInd?=?1?+?（1:trainWeekNum）;

testWeekX?=?[];
testWeekY?=?[];
for?yWeekInd?=?testWeekInd
????yWeekDayInd?=?（yWeekInd*7-6）:（yWeekInd*7）;
????xWeekDayStart?=?yWeekInd?*?7?+?1;
????xWeekDayEnd?=?（yWeekInd?+?1）?*?7;
????xWeekDayInd?=?xWeekDayStart:xWeekDayEnd;
????yDayData?=?QLD1（:?yWeekDayInd）;
????xDayData?=?QLD1（:?xWeekDayInd）;????
????testWeekY?=?[testWeekY?yDayData‘];
????testWeekX?=?[testWeekX?xDayData‘];
end

trainWeekX?=?[];
trainWeekY?=?[];
for?yWeekInd?=?trainWeekInd
????yWeekDayInd?=?（yWeekInd*7-6）:（yWeekInd*7）;
????xWeekDayStart?=?yWeekInd?*?7?+?1;
????xWeekDayEnd?=?（yWeekInd?+?1）?*?7;
????xWeekDayInd?=?xWeekDayStart:xWeekDayEnd;
????yDayData?=?QLD1（:?yWeekDayInd）;
????xDayData?=?QLD1（:?xWeekDayInd）;????
????trainWeekY?=?[trainWeekY?yDayData‘];
????trainWeekX?=?[trainWeekX?xDayData‘];
end

nets?=?{};
netMapes?=?[];

for?time?=?1:48
????disp（[‘?time:‘?num2str（time）]）;

????testInd??=?（0:（testWeekNum-1））??*?48?+?time;
????trainInd?=?（0:（trainWeekNum-1））?*?48?+?time;

????global?trainX?trainY?xmap?ymap?testX?testY;

????testX??=?testWeekX（:?testInd）;
????testY??=?testWeekY（:?testInd）;
????trainX?=?trainWeekX（:trainInd）;
????trainY?=?trainWeekY（:trainInd）;

????[trainX?xmap]?=?mapminmax（trainX?0.0000001?1）;
????[trainY?ymap]?=?mapminmax（trainY?0.0000001?1）;
????testX?=?mapminmax（‘apply‘?testX?xmap）;

????[bestGam?bestSig2]?=?optimizeLSSVM（）;
????rand（‘seed‘?2）;
????net?=?initlssvm（trainX‘?trainY‘?‘function?estimation‘?bestGam?bestSig2?‘RBF_kernel‘）;
????net?=?trainlssvm（net）;
????ySim?=?simlssvm（net?testX‘）‘;
????ySim?=?mapminmax（‘reverse‘?ySim?ymap）;
????mape_?=?mape（testY?ySim）;

????nets{time?1}?=?net;
????netMapes?=?[netMapes?mape_];

end

meanMape?=?mean（netMapes）

save?nets?nets;

????

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2016-08-15?21:25??lssvm+pso\
?????文件????????2792??2016-08-15?21:20??lssvm+pso\main.m
?????文件????????1835??2016-08-15?21:24??lssvm+pso\main_back.m
?????文件?????????108??2016-08-15?21:07??lssvm+pso\mape.m
?????文件?????1818832??2016-08-15?21:23??lssvm+pso\nets.mat
?????文件?????????671??2016-08-15?21:21??lssvm+pso\optimizeLSSVM.asv
?????文件?????????671??2016-08-15?21:21??lssvm+pso\optimizeLSSVM.m
?????文件????????4557??2016-08-15?21:12??lssvm+pso\PSO.m
?????文件??????292213??2016-08-15?21:07??lssvm+pso\QLD1.mat