Problem with non-linear fit

2 次查看（过去 30 天）

显示更早的评论

R7 DR 2015-10-9

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/247714-problem-with-non-linear-fit

评论： Star Strider 2015-10-9

R7 DR Matlab.xlsx

在 MATLAB Online 中打开

Hi I am trying to fit the data and find the constant values. my code is...

[T]=xlsread('Matlab.xlsx','sheet2','C5:C2685')
[alpha]=xlsread('Matlab.xlsx','sheet2','I5:I2685')%time
[dalpha_dt]=xlsread('Matlab.xlsx','sheet2','J5:J2685')
    F=ones(size(alpha));
    F=(1-alpha) 
    coeff0=[2.17E+22, 5] % initial guess
    coeff=nlinfit([T,F],dalpha_dt,@model,coeff0);
    A=coeff(:,1)
    n=coeff(:,2)

Function:

function dhat=model(coef,a)
% par_fit = [a b]
  a=coef(1);
  b=coef(2);
  T=a(:,1);
  F=a(:,2);
  % predicted model
  dhat=a.*exp(208000./(8.3147*(T+273))).*(F^b);
  return

I need to find the new coefficient values, but it is showing following error..Please tell me how to resolve this.

Error using nlinfit (line 205)
Error evaluating model function 'model'.
  Error in fitting (line 16)
coeff=nlinfit([T,F],dalpha_dt,@model,coeff0);
Caused by:
    Attempted to access a(:,2); index out of bounds because numel(a)=1.

Thanks

回答（2 个）

Star Strider 2015-10-9

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/247714-problem-with-non-linear-fit#answer_195353

You defined ‘a’ as a scalar (appropriately) so it is by definition a (1x1) ‘array’ (taking liberties with the concept here). It doesn’t have a second dimension.

How do you want to define ‘T’ and ‘F’?

11 个评论
显示 9更早的评论隐藏 9更早的评论

Star Strider 2015-10-9

在 MATLAB Online 中打开

My response to R7 DR’s ‘Answer’ ...

‘The equations is... dalpha_dt= A*exp(-208000/(8.3417*(T+273)*(F^n)’

The negative sign (that just now appeared) of course makes a huge difference here!

The revised objective function is:

model = @(b,TF) b(1).*exp(-208000./(8.3147*(TF(:,1)+273))).*(TF(:,2).^b(2));

I cannot get the function to provide what I consider to be an acceptable fit. You will have to provide a vector of initial parameter estimates that will converge on a solution that gives an appropriate fit to your data.

Nonlinear parameter estimation is inherently somewhat heuristic. You have to experiment to choose a set of initial parameter estimates that are close enough to the ‘correct’ ones so that your function will converge on the ‘correct’ final estimates, and not diverge or converge on a ‘local minimum’. (A genetic algorithm may be the best way to generate an appropriate set of initial parameter estimates for this problem.)

I got your objective function working correctly for you, so I leave the rest of this experiment to you.

R7 DR 2015-10-9

Thank for the information.

I will try to find the solution using genetic algorithms. If I need any help I will come back to you.

Thanks for your time. Have a nice weekend.

Star Strider 2015-10-9

My pleasure.

You, too!

请先登录，再进行评论。

R7 DR 2015-10-9

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/247714-problem-with-non-linear-fit#answer_195374

在 MATLAB Online 中打开

The idea is that, I have data generated from the experiment. I can also calculate same kind of data from mathematical equation which is depended on two coefficients. Now I need to find these coefficients by fitting the mathematical data with experimental data.

The equations is...dalpha_dt= A*exp(-208000/(8.3417*(T+273)*(F^n)

                          T=loaded from the excel.
                          F=loaded from excel.
                          A & n are the coefficients I want to find.

I made the same calculation using excel with an initial guess of 'A & n' and the curves look like the following image.