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Alex Sha


Last seen: Today Con actividad desde 2019

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  • 12 Month Streak
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problem in curve fitting using summation of sine functions
@nihal if don't mind fitting function other than summation of sine, much better result will be achieved. For phi_dot data: R...

alrededor de 2 meses hace | 0

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Respondida
Exp Fit Error: Error using fit>iFit (line 340) NaN computed by model function, fitting cannot continue. Try using or tightening upper and lower bounds on coefficients.
There are two solutions: 1: Sum Squared Error (SSE): 0.0371625579290083 Root of Mean Square Error (RMSE): 0.0609611006536204 ...

alrededor de 2 meses hace | 0

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Possibly spurious solutions - Matlab blocked with no answers
There is a approximate solution for original equations: p2: 35001350.3279785 p3: 35113789.3799513 u2: -8.90075607998193 u3: ...

2 meses hace | 0

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Interpolation schemes that produce positive second derivatives of the interpolant
How about to replace interpolation with a fitting function, which ensure non-negative second derivatives: 1: For data: x = [...

3 meses hace | 0

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How to find the equation of the data available of a graph?
Try the fitting function below: Sum Squared Error (SSE): 1.05153845767184 Root of Mean Square Error (RMSE): 0.17850714760936...

3 meses hace | 0

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can help me to found empirical equation for data L1 vs T1
How about the one below, much simple and works well: Sum Squared Error (SSE): 0.348116593172766 Root of Mean Square Error (R...

4 meses hace | 2

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can help me to found empirical equation for data L1 vs T1
It is not easy to find a function to describe the curve. Refer to the fitting function and result below: Sum Squared Error (S...

4 meses hace | 1

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how to fit the coupled differential equations and get the coefficients?
Refer to the results below: Sum Squared Error (SSE): 46715596564.0427 Root of Mean Square Error (RMSE): 35062.1990798768 Corr...

5 meses hace | 0

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Derivative not working plot
Unfortunately, the "exp2" fitting result below given by Matlab is not correctly. theFit = General model Exp2: theF...

5 meses hace | 0

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curve fitting exponential function with two terms
If taking the fitting function as: y=a*exp(b*x) + c*exp(d*x); and also taking the data like below directly; x = [6500 6350 580...

5 meses hace | 0

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Damped Oscillation Equation Fitting
if taking fitting function as: x=a*exp(-b*t)*sin(w*t+phi) for trial-1 Sum Squared Error (SSE): 9.1948847955911E-5 Root of Mea...

6 meses hace | 0

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Fitting a model to my data using non linear least square fit method
The best solution: Root of Mean Square Error (RMSE): 0.0143800358786989 Correlation Coef. (R): 0.998885623657614 R-Square: 0....

7 meses hace | 0

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Fsolve don't work good with trigonometric
There are some solutions like below No. 1 2 3 4 5 xa1 0.835289443057692 1.97769580537186 0.119396464246135 0.813305799520437 0...

8 meses hace | 0

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fsolve result is not desirable even giving a close starting point
For Qingbin's equations, although it is a problem that has passed a long time, it is worth and interesting to have a try, there ...

8 meses hace | 0

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using lsqnonlin with multiple functions
@joshua payne refer to the results below Sum Squared Error (SSE): 0.377485784540046 Root of Mean Square Error (RMSE): 0.082102...

9 meses hace | 0

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Least squares linear regression with constraints
If using direct nonlinear fitting a1 59.737732722511 a2 2.72067588034148 a3 -0.192039313150924 Whi...

9 meses hace | 0

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How do I curve fit the data set
@Prajwal Magadi, one more function: Sum Squared Error (SSE): 75571.6557870726 Root of Mean Square Error (RMSE): 2.7490299341...

9 meses hace | 1

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fitting data with a combination of exponential and linear form ( a*exp(-x/b)+c*x+d )
If taking fitting function as "y=a*exp(-x/b)+c*x+d", the result will be: Sum Squared Error (SSE): 0.473516174967249 Root of Me...

10 meses hace | 1

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Fitting multiple exponential function .
@Saroj Poudyal, the result you obtained is not the best one, refer to the global optimization solution below: Sum Squared Error...

11 meses hace | 1

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How to fit multiple gaussian in a curve ?
For the summation of 6 Gaussians function: Sum Squared Error (SSE): 2.61218021364296E-9 Root of Mean Square Error (RMSE): 4.49...

alrededor de 1 año hace | 0

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Curve fitting the data series
Refer to the results below, should be the unique global solution: Sum Squared Error (SSE): 0.0378758633912789 Root of Mean Squ...

alrededor de 1 año hace | 1

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Non-linear Multi-Variable Fitting
If possible, post out your data file please

más de 1 año hace | 0

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Genetic Algorithm not returning best found solution
Taking my experience, GA is not an efficient and ideal global optimization algorithm, in lots of cases, GA like random reserach ...

más de 1 año hace | 0

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Solving a system of Non-linear Equations with Complex numbers
There are much more solutions else: x1: 5000+3401.68025708298i x2: 5000-3401.68025708301i x3: -3.62536433474507+0i x1: 5...

más de 1 año hace | 0

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How do I fit a regression equation to find coefficients and exponents?
Although the results may seem strange, mathematically speaking, the result below is the best one: Sum Squared Error (SSE): 87...

más de 1 año hace | 0

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How to constraint the values of fitted parameters with lsqcurvefit?
hi, the result is good enough Sum Squared Error (SSE): 0.0105245967805521 Root of Mean Square Error (RMSE): 0.01938758511131 ...

casi 2 años hace | 1

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Respondida
curve fitting tool custom equation
if taking only part of data, for example, from No. 105 to No. 300, then the result will looks good Sum Squared Error (SSE): 111...

alrededor de 2 años hace | 0

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The fsolve function fails to give me an answer for seven unknowns. What should I do?
Just doing some equivalent deformation (change division into multiplication), for example, form: f(5)=((x(1)^3)*(x(2))/(x(4)*...

alrededor de 2 años hace | 0

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How to curve fit an equation that gets values from another equation?
How about the results below: Residual Sum of Squares (RSS): 34.9122402573179 Root of Mean Square Error (RMSE): 0.9585109100402...

alrededor de 2 años hace | 0

Respondida
Unable to find explicit solution
One solution seems to be: t: -8.33315732250827

más de 2 años hace | 0

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