Trial and error problem
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Dear Matlab Community Members
My objective is to find the values a, b, and c. of the following equation:
log(m)=log(a)+(b/(T-c))
I have three values of m & T
m=0.0701 & T=293.65
m=0.0262 & T=313.15
m=0.00433 & T=373.15
I want to know what is the best code or technique to find these values.
Thank you very much
8 个评论
Torsten
2023-1-26
So you have one data point m=0.0262, T=313.15 and you want to find parameters a, b and c such that log(m)=log(a)+(b/(T-c)) ?
Ahmad Al-Issa
2023-1-26
Torsten
2023-1-26
Why not a = m, b = 0, c = arbitrary ?
But seriously: If you have many data points for m and T, you can use a fitting tool to fit the constants.
But adjusting three parameters with only one data point doesn't make sense since the (almost arbitrary) parameters for this single data point will most probably not work for a second one.
Ahmad Al-Issa
2023-1-26
编辑:Ahmad Al-Issa
2023-1-26
Torsten
2023-1-26
actually, I use the value of m and T only for one time because it is measured experimentally.
after finding a, b, and c, I will use the equation to find m at any T.
As I tried to explain in my response, exactly this doesn't make sense since you only have one measurement point.
Ahmad Al-Issa
2023-1-26
编辑:Ahmad Al-Issa
2023-1-26
How did you choose that function for the fit? It seems like a poor one, because of the singularity that will happen when T==c.
c = 280;
T = 260 : 380;
f = @(t) 1./(t -c);
plot(T,f(T))
Even if your values of T are strictly greater than c, (the "critical" temperature), this behavior will make it difficult for any algorithm to fit it.
One can try (e.g. with fitnlm), but MATLAB spits out warnings about overparameterization, and the fit is not good.
Ahmad Al-Issa
2023-1-26
编辑:Ahmad Al-Issa
2023-1-27
回答(1 个)
The results are not convincing, but that's the way to go with three data points.
fun1 = @(x)[0.0701-x(1)*exp(x(2)/(293.65-x(3)));0.0262-x(1)*exp(x(2)/(313.15-x(3)));0.00433-x(1)*exp(x(2)/(373.15-x(3)))];
fun2 = @(x)[log(0.0701)-(log(x(1))+x(2)/(293.65-x(3)));log(0.0262)-(log(x(1))+x(2)/(313.15-x(3)));log(0.00433)-(log(x(1))+x(2)/(373.15-x(3)))];
x0 = [2 1 450];
x = fsolve(fun1,x0)
fun1(x)
x = fsolve(fun2,x0)
fun2(x)
5 个评论
"Not convincing", indeed. :-)
% The data
m = [0.0701;
0.0262;
0.0043];
T = [293.65;
313.15;
373.15];
% Solve for the coefficients at the data points
x0 = [2 1 450];
fun2 = @(x)[log(m(1))-(log(x(1))+x(2)/(T(1)-x(3)));
log(m(2))-(log(x(1))+x(2)/(T(2)-x(3)));
log(m(3))-(log(x(1))+x(2)/(T(3)-x(3)))];
x = fsolve(fun2,x0) % these are the coefficents
% The resulting fitted function to get log(m) from T
fun_fsolve = @(t) log(x(1))+x(2)./(t-x(3));
% Calculate the predicted values in the region of the data
T0 = 290:390;
logm_fsolve = fun_fsolve(T0);
% Plot the data and the fit
figure
hold on
plot(T,log(m),'*')
plot(T0,logm_fsolve,'r')
legend('data','fsolve')
Ahmad Al-Issa
2023-1-26
编辑:Ahmad Al-Issa
2023-1-27
Seems to work - I'm surprised about the symbolic solver:
m1=0.0701;
T1=293.65;
m2=0.0262;
T2=313.15;
m3=0.00433;
T3=373.15;
syms a b c
eqns = [log(a)+b/(T1-c)== log(m1), log(a)+b/(T2-c)== log(m2), log(a)+ b/(T3-c)==log(m3)];
S = vpasolve(eqns,[a b c])
double(subs([log(a)+b/(T1-c)- log(m1), log(a)+b/(T2-c)- log(m2), log(a)+ b/(T3-c)-log(m3)],[a b c],[S.a,S.b,S.c]))
Ahmad Al-Issa
2023-1-27
Isn't the form of the equation usually
m = 10^(A-B/(C+T))
where T is in degreeC ?
Thus
log10(m) = A - B/(T+C)
where log10 is not the natural, but the decadic logarithm and T is temperature in degreeC ?
m1=0.0701;
T1=293.65-273.15;
m2=0.0262;
T2=313.15-273.15;
m3=0.00433;
T3=373.15-273.15;
syms a b c
eqns = [a-b/(T1+c)== log10(m1), a-b/(T2+c)== log10(m2), a-b/(T3+c)==log10(m3)];
S = vpasolve(eqns,[a b c])
double(subs([a-b/(T1+c)- log10(m1), a-b/(T2+c)- log10(m2), a-b/(T3+c)-log10(m3)],[a,b,c],[S.a,S.b,S.c]))
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