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Alex Sha


Last seen: Today |  2019 年からアクティブ

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  • Knowledgeable Level 4
  • 12 Month Streak
  • Revival Level 3
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Solution of system of nonlinear equations
@Swami Between the range [0,1] you specified, most likely, there should be no real numbers solution，an approximate solution is: ...

約1ヶ月 前 | 0

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Why is Curve fitting tool not giving good results even with the R-square value of 0.99?
@Muhammad Arsal the goodness of a fitting should be judged by SSE (Sum of Squared Error), but not R-Square value, the former rep...

約2ヶ月 前 | 0

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Non-linear Algebraic 36 equations unsloved
@MINATI PATRA please giving out the code you used, or the detail description of your 36 equations

7ヶ月 前 | 0

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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...

9ヶ月 前 | 0

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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 ...

9ヶ月 前 | 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: ...

9ヶ月 前 | 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 = [...

10ヶ月 前 | 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...

10ヶ月 前 | 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...

11ヶ月 前 | 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...

11ヶ月 前 | 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...

約1年 前 | 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...

約1年 前 | 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...

約1年 前 | 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...

約1年 前 | 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....

約1年 前 | 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...

約1年 前 | 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 ...

約1年 前 | 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...

1年以上 前 | 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...

1年以上 前 | 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...

1年以上 前 | 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...

1年以上 前 | 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...

1年以上 前 | 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...

1年以上 前 | 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...

1年以上 前 | 1

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

2年弱 前 | 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 ...

2年弱 前 | 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...

約2年 前 | 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...

約2年 前 | 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 ...

2年以上 前 | 1

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回答済み
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...

2年以上 前 | 0

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