CPI指数的分析及预测

保证书我们仔细阅读了中国大学生数学建模竞赛的竞赛规则,我们完全明白在竞赛开始后不能以任何方式与队外的任何人（包括指导教师）讨论竞赛题的求解问题,抄袭别人的成果也是违反竞赛规则的,如被发现将会受到严肃处置。我们也知道如果引用别人的成果或其他公开的资料（包括网上查到的资料）必须按照规定的参考文献的表述方式在正文和参考文献中明确列出。为了确保竞赛的公正、公平性,我们保证严格遵守竞赛规则。参赛报名号：参赛队员：指导老师参赛评阅编号：全国统一编号：3#【8】张志涌、刘瑞桢、杨祖樱掌握和精通MATLAB【M】北京北京航空航天大学出版社1997【9】徐全智、杨晋浩数学建模北京高等教育出版社2003九、附件附录月份01年02年0年30年40年50年60年70年809年1年01年1年年年年年年年年11.20%-1%0.40%3.20%1.90%1.90%2.20%7.10%1%1.50%4.90%2000.20%2.10%3.90%0.90%2.70%8.70%-2.70%4.90%1.60%30.80%-0.90%3%2.70%0.80%3.30%8.30%-2.40%5.40%0.80%1.70%41.60%-1%3.80%1.80%1.20%3.00%8.50%-2.80%5.30%1.30%1.50%51.70%-0.70%4.40%1.80%1.40%3.40%7.70%-3.10%5.50%1.10%1.40%61.40%-0.30%5%1.60%1.50%4.40%7.10%-2.90%6.40%0.80%1.70%71.50%-0.50%5.30%1.80%1%5.60%6.30%-3.30%6.50%0.90%1.80%81%-0.90%5.30%1.30%1.30%6.50%4.90%-3.50%0.70%1.20%9--1.10%5.20%0.90%1.50%6.20%4.60%3.60%0.10%0.70%0.80%100.20%-1.80%4.30%1.20%1.40%6.50%4%-4.40%0.80%0.50%11--3%2.80%1.30%1.90%6.90%2.40%0.60%5.10%0.30%0.70%12--3.20%2.40%1.60%2.80%6.50%1.50%1.90%4.60%0.60%0.40%0.70%-1%1.17%3.90%1.82%1.47%4.80%5.90%-3.30%CPI0.70%附录二：y=[0.6;1.9;1.5;2.7;2.4;2.8;3.1;2.9;3.3;3.5;3.6;4.4;5.1;7.6;4.9;4.9;5.4;5.3;5.5;5.4];x1=[3.25.33.76.25.25.96.15.76.87.5810.111.79.610.31111.711.511.714.4]x2=[-1.2-0.8-0.4-1.3-1.1-1.3-1.2-1-0.8-1.2-1.5-1.3-0.70.1-0.20.40.81.41.32.1]x3=[1.62.22.32.42.52.83.23.23.33.33.43.7443.233.23.23.23.4]x4=[-2.2-1.5-0.50.1000.1-0.3-0.7-0.6-0.7-0.5-0.7-0.7-0.2-0.30.10.50.70.9]x5=[-0.6-0.3-1.20.80.30.40.60.91.11.21.20.90.60.710.30.50.50.50.6]x6=[-1.21.52.533.34.5554.84.44.34.95.866.86.16.66.16.16.2]y=[0.6;1.9;1.5;2.7;2.4;2.8;3.1;2.9;3.3;3.5;3.6;4.4;5.1;7.6;4.9;4.9;5.4;5.3;5.5;5.4];>>X二[ones(20,l)xl'x2'x3'x4'x5'x6'(xl."2)'(x3「2)'(x4「2)'];>>[b,bint,r,rint,stat]=regress(y,X,0.05)b=l9.6l89l.507ll.l303-l6.8642-0.74830.l0870.9677-0.09l90.53002.7308-0.5449-0.067l-0.0235bint=0.050239.l8770.46632.54790.3674l.8932-34.05830.3299-2.33740.8409-0.8950l.ll24-2.l5944.0949-0.l548-0.0290-0.24390.3197-2.1724-0.8596-0.25071.30395.14191.08260.72550.2037r=-0.03970.0682-0.0110-0.06660.1607-0.03850.0917-0.1903-0.23700.16530.06310.0637-0.39370.36980.05350.07310.1690-0.66920.19240.1756rint-0.2140-0.4014-0.0462-0.5094-0.5107-0.5909-0.5685-0.9072-0.9118-0.6136-0.5960-0.6142-0.73130.3022-0.4615-0.6333-0.49710.13460.53790.02420.37620.83200.51390.75190.52650.43780.94430.72210.7415-0.05610.43740.56850.77950.8351-0.9334-0.4050-0.20470.58960.00060.3507Stat=0.981230.41930.0001

灰色模型程序：

FunctionGM1=fungry1(x0)T=input('T=');X1=zeros(1,length(x0));B=zeros(length(x0)-1,2);

yn=zeros(length(x0)-1,1);Hatx0=zeros(1,length(x0)+T);

Hatx00=zeros(1,length(x0));Hatx1=zeros(1,length(x0)+T);Epsilon=zeros(length(x0),1);omega=zeros(length(x0),1);Fori=1:length(x0)Forj=1:i

x1(i)=x1(i)+x0(j);EndEndFori=1:length(x0)-1B(i,1)=(-1/2)*(x1(i)+x1(i+1));B(i,2)=1;

yn(i)=x0(i+1);

EndHatA=(inv(B'*B))*B'*ynFork=1:length(x0)+T

Hatx1(k)=(x0(1)-HatA(2)/HatA(1))*exp(-HatA(1)*(k-1))+HatA(2)/HatA(1);

EndHatx0(1)=Hatx1(1);Fork=2:length(x0)+THatx0(k)=Hatx1(k)-Hatx1(k-1);EndFori=1:length(x0)Epsilon(i)=x0(i)-Hatx0(i);Omega(i)=(epsilon(i)/x0(i))*100;End%x0,Hatx1,Hatx0,epsilon,omega,c=std(epsilon)/std(x0);p=0;Fori=1:length(x0)Ifabs(epsilon(i)-mean(epsilon))<0.6745*std(x0)p=p+1;

End

End

p=p/length(x0)Ifp>0.95&c<0.35

disp('Themodelisgoodandtheforecastis:'),

disp(Hatx0(length(x0)+T))

Elseifp>0.85&c<0.5

disp('Themodeliseligibilityandtheforecastis:'),

disp(Hatx0(length(x0)+T))

Elseifp>0.70&c<0.65

disp('Themodelisnotgoodandtheforecastis:'),

disp(Hatx0(length(x0)+T))

Elsep<=0.70&c>0.65

disp('Themodelisbadandtryagain')

Endfori=1:length(x0)

Hatx00(i)=Hatx0(i);

Endz=1:length(x0);Plot(z,x0,'-',z,Hatx00,':')Text(2,x0(2),'Historydata:realline')Text(length(x0)/2,Hatx00(length(x0))/2,'Simulationdata:broken

line')

EndX0=[-1.21.52.533.34.5554.84.44.34.95.866.86.16.66.16.16.2];Fungry1(x0);T=1

HatA=

-0.0439

3.2091

p=

0.9500Them