lingo嵌套for的分段函数求解答!!!!
sets:index/1..15/:PE,alpha,beta,rho;
index2/1..16/:P,phi;
endsets
data:
pi=3.141592653589;
l1=1;
l4=4;
enddata
min=@sum(index(i):(PE(i)-P(i))^2);
l2=x2;
l3=x3;
@for(index(i):@if((phi(i))#le#pi,
P(i)=pi-alpha(i)-beta(i),
P(i)=pi-alpha(i)+beta(i)));!问题出在这一块
@for(index(i):
@cos(alpha(i))=(rho(i)^2+l3^2-l2^2)/(2*rho(i)*l3));
@for(index(i):
@cos(beta(i))=(rho(i)^2+l4^2-l1^2)/(2*rho(i)*l4));
@for(index(i):
rho(i)=(l1^2+l4^2-2*l1*l4*@cos(phi(i)))^(0.5));
@cos(phi(16))=((l1+l2)^2+l4^2-l3^2)/(2*l4*(l1+l2));
@cos(P(16))=((l1+l2)^2-l4^2-l3^2)/(2*l4*l3);
@for(index(i):
PE(i)=P(16)+(phi(i)-phi(16))^2*2/(3*pi));
@for(index(i):
phi(i)=phi(16)+pi*i/(2*15));
x2^2+x3^2+x2*x3*(2^0.5)-25<=0;
-x2^2-x3^2+x2*x3*(2^0.5)+9<=0;
end
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
想写一个if中嵌套for的分段函数,分段函数如下
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
函数的图片上传一下
ilikenba 发表于 2022-12-24 07:26 static/image/common/back.gif
函数的图片上传一下
pu(i)=pai-alpha(i)-beta(i) (phi(i)<=pai)
pu(i)=pai-alpha(i)+beta(i) (phi(i)>pai)
ilikenba 发表于 2022-12-24 07:26 static/image/common/back.gif
函数的图片上传一下
函数长这样,求助大佬怎么编写
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