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### Solve the Coefficient of ODES ...

November 10 2014
0 1

Dear Friends,

My present problem is to calculate the coefficients

of ODES based on the experiment data. In order to simulate the actual experiment, a set of  is given with . Then the experiment data (yexp) can be calculated. Finally, the least-squares method (lsq) is used to calculate the coefficient values. Now the NLPSolve function can be used. However, the globalsolve cant run.

If it is convenient for you, wish you can solve it.

Code:

restart;
cdm_ode := diff(y1(t), t) = c0*(y6(t)*(1-y3(t))/(s0*(1-y4(t)*(1-y5(t)))))^n/(1-y2(t)), diff(y2(t), t) = ks*y2(t)^(1/3)*(1-y2(t)), diff(y3(t), t) = h1*(1-y3(t)/h2)*c0*(y6(t)*(1-y3(t))/(s0*(1-y4(t)*(1-y5(t)))))^n/(sigma*(1-y2(t))), diff(y4(t), t) = (1/3)*kp*(1-y4(t))^4, diff(y5(t), t) = A*B*y1(t)^(B-1)*c0*(y6(t)*(1-y3(t))/(s0*(1-y4(t)*(1-y5(t)))))^n/(1-y2(t)), diff(y6(t), t) = y6(t)*c0*(y6(t)*(1-y3(t))/(s0*(1-y4(t)*(1-y5(t)))))^n/(1-y2(t));

tol_t := 3600;
sol := dsolve([cdm_ode, y1(0) = 0, y2(0) = 0, y3(0) = 0, y4(0) = 0, y5(0) = 0, y6(0) = 175], numeric, range = 0 .. tol_t, output = listprocedure, parameters = [c0, n, sigma, s0, ks, h1, h2, kp, A, B]);

sol(parameters = [5.7*10^(-6), 10.186, 175, 200, 5*10^(-8), 10000, .269, 1.5*10^(-7), 1.5, 2]);

t := [seq(i^2, i = 0 .. 50, 1)];

y1data := subs(sol, y1(t));

y1exp := [seq(y1data(t[i]), i = 1 .. 51)];

err := proc (c0, n, s0, ks, h1, h2, kp, A, B) local y1cal, y1val, lsq; sol(parameters = [c0, n, 175, s0, ks, h1, h2, kp, A, B]); y1cal := subs(sol, y1(t)); y1val := [seq(y1cal(t[i]), i = 1 .. 51)]; lsq := add((y1val[i]-y1exp[i])^2, i = 1 .. 51); lsq end proc;

with(Optimization);
val := NLPSolve(err, 10^(-8) .. 10^(-4), 2 .. 20, 150 .. 250, 10^(-2) .. 1, 100 .. 20000, 10^(-5) .. .4, 10^(-5) .. 1, .5 .. 2, 1 .. 10);
GlobalSolve(err, 10^(-10) .. 10^(-4), 2 .. 20, 150 .. 250, 0 .. 1, 100 .. 15000, 0 .. .5, 0 .. 1, .5 .. 2, 1 .. 5);

Error, (in GlobalOptimization:-GlobalSolve) `InertForms` does not evaluate to a module

### Global Optimization - XYZ problem...

February 05 2014
0 4

Data.xlsx

XYZ.mw

Hello,

I'm using the Global Optimization Toolbox to solve some examples and fit equations to a given data, finding "unknown" parameters. I generated the data on Excel, and I already know the values of these parameters.

The XY case is (there is no problem here, I just put as a example I follow):

> with(GlobalOptimization);
> with(plots);

> X := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "I5:I25");
> Y := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "J5:J25");

> XY := zip( (X, Y) -> [X, Y] , X, Y);
> fig1 := plot(XY, style = point, view = [.9 .. 3.1, 6 .. 40]);

> Model := A+B*x+C*x^2+D*cos(x)+E*exp(x):
> VarInterv := [A = 0 .. 10, B = 0 .. 10, C = -10 .. 10, D = 0 .. 10, E = 0 .. 10];

> ModelSubs := proc (x, val)

subs({x = val}, Model)

end proc;

> SqEr := expand(add((ModelSubs(x, X(i))-Y(i))^2, i = 1 .. 21));
> CoefList := GlobalSolve(SqEr, op(VarInterv), timelimit = 5000);

> Model := subs(CoefList[2], Model):

I could find the right values of A, B, C, D and E.

My problem is in the XYZ case, where I don't know how to "write" the right instruction. My last attempt was:

> with(GlobalOptimization);
> with(plots);

> X := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "Q5:Q25"); X2 := convert(X, list);
> Y := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "R5:R25"); Y2 := convert(Y, list);
> Z := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "S5:S25"); Z2 := convert(Z, list);
> NElem := numelems(X);

> pointplot3d(X2, Y2, Z2, axes = normal, labels = ["X", "Y", "Z"], symbol = box, color = red);

> Model := A*x+B*y+C*sin(x*y)+D*exp(x/y);

> VarInterv := [A = 0 .. 10, B = 0 .. 10, C = 0 .. 10, D = 0 .. 10];

> ModelSubs:=proc({x,y},val)

subs({(x,y)=val},Model)

end proc:
Error, missing default value for option(s)

> SqEr := expand(add((ModelSubs(x, y, X(i), Y(i))-Z(i))^2, i = 1 .. NElem));
> CoefList := GlobalSolve(SqEr, op(Range), timelimit = 5000);
Error, (in GlobalOptimization:-GlobalSolve) finite bounds must be provided for all variables

My actual problem involves six equations, six parameters and four or five independent variables on each equation, but I alread developed a way to solve two or more equations simultaneously.

Thanks

### Global Optimization - XYZ problem...

February 05 2014
0 0

Hello,

I'm using the Global Optimization Toolbox to solve some examples and fit equations to a given data, finding "unknown" parameters. I generated the data on Excel, and I already know the values of these parameters.

The XY case is (there is no problem here, I just put as a example I follow):

> with(GlobalOptimization);
> with(plots);

> X := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "I5:I25");
> Y := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "J5:J25");

> XY := zip( (X, Y) -> [X, Y] , X, Y);
> fig1 := plot(XY, style = point, view = [.9 .. 3.1, 6 .. 40]);

> Model := A+B*x+C*x^2+D*cos(x)+E*exp(x):
> VarInterv := [A = 0 .. 10, B = 0 .. 10, C = -10 .. 10, D = 0 .. 10, E = 0 .. 10];

> ModelSubs := proc (x, val)

subs({x = val}, Model)

end proc;

> SqEr := expand(add((ModelSubs(x, X(i))-Y(i))^2, i = 1 .. 21));
> CoefList := GlobalSolve(SqEr, op(VarInterv), timelimit = 5000);

> Model := subs(CoefList[2], Model):

I could find the right values of A, B, C, D and E.

My problem is in the XYZ case, where I don't know how to "write" the right instruction. My last attempt was:

> with(GlobalOptimization);
> with(plots);

> X := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "Q5:Q25"); X2 := convert(X, list);
> Y := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "R5:R25"); Y2 := convert(Y, list);
> Z := ExcelTools:-Import("F:\\Data.xlsx", "Plan1", "S5:S25"); Z2 := convert(Z, list);
> NElem := numelems(X);

> pointplot3d(X2, Y2, Z2, axes = normal, labels = ["X", "Y", "Z"], symbol = box, color = red);

> Model := A*x+B*y+C*sin(x*y)+D*exp(x/y);

> VarInterv := [A = 0 .. 10, B = 0 .. 10, C = 0 .. 10, D = 0 .. 10];

> ModelSubs:=proc({x,y},val)

subs({(x,y)=val},Model)

end proc:
Error, missing default value for option(s)

> SqEr := expand(add((ModelSubs(x, y, X(i), Y(i))-Z(i))^2, i = 1 .. NElem));
> CoefList := GlobalSolve(SqEr, op(Range), timelimit = 5000);
Error, (in GlobalOptimization:-GlobalSolve) finite bounds must be provided for all variables

My actual problem involves six equations, six parameters and four or five independent variables on each equation, but I alread developed a way to solve two or more equations simultaneously.

Thanks.

### New global optimization toolbox...

May 08 2013 Maple Global Optimization
3
0

We have just released a new, more powerful version of the Maple Global Optimization Toolbox.

For this new release, Maplesoft has partnered with Noesis Solutions to develop a new version of the Maple Global Optimization Toolbox that is powered by Optimus technology. Optimus, from Noesis Solutions, is a platform for simulation process integration and design optimization that includes powerful optimization algorithms. This advanced technology is now available...

### How to deal with the error：(in GlobalOptimization:...

March 13 2012
0 0

Hi,

The error showed up whenever I tried to do the Maximum Likelihood Estimation with Global Optimization Toolbox.My objective (likelihood ) function f is defined as follows(A1 to A5 are intermediate variables; parameters  are x[1] to x[12]）:

f := 0;

for j from 1 by 1 to 21 do

A1 := exp(x[1]+x[2]*c[j]);

A2 := exp(x[3]+x[4]*c[j]);

### An optimal day...

February 09 2009 Global Optimization
0
0

Yesterday was one of those remarkable days when everything seems just about right. The highlight was an email message I received from a Prof. Fang from Ryerson University notifying us that we had been both nominated and awarded the Omond Solandt Award by the Canadian Operational Research Society for ongoing and outstanding contribution to the field of Operations Research (OR). No, it’s not a Nobel Prize or an Oscar, but whenever a group of smart people publically recognize our work, the honor and pride are genuine.

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