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Я хочу сопоставить данные с моей пользовательской функцией для вычисления параметров модели. Данные по x и y прилагаются в конце. Пользовательская функция:

 y=a (-((4/3)*3.14*((60e-10)^3-((60e-10)-x).^3).*b*(c-1096)/c 4*3.14*(60e-10)^2.*(d.*((60e-10)-x).^2/(60e-10)^2 e (f-e-d.*((60e-10)-x).^2/(60e-10)^2).*exp(-x./g)))/(1e3*1.38e-23*1090))
  

и параметры имеют ограничения и инициалы:

 -inf<a<inf,    a=2e4
1e11<b<1e12,   b=7.8e11
1120<c<1300,   c=1200
70<d<130,      d=127
300<e<700,     e=680
400<f<900,     f=850
1e-10<g<3e-10, g=2.5e-10
  

Тем не менее, я пробовал matlab и rigin для подгонки данных к модели, но все они не смогли найти подходящего варианта. Я признателен, если вы можете предоставить какие-либо предложения. На самом деле, я понимаю, что параметров слишком много, и я также попытался исправить параметры b, d, e и g, освободив другие, но по-прежнему без хороших результатов.

 x=[3.70400000000000e-10
    3.80400000000000e-10
    3.90400000000000e-10
    4.00400000000000e-10
    4.10400000000000e-10
    4.20400000000000e-10
    4.30400000000000e-10
    4.40400000000000e-10
    4.50400000000000e-10
    4.60400000000000e-10
    4.70400000000000e-10
    4.80400000000000e-10
    4.90400000000000e-10
    5.00400000000000e-10
    5.10400000000000e-10
    5.20400000000000e-10
    5.30400000000000e-10
    5.40400000000000e-10
    5.50400000000000e-10
    5.60400000000000e-10
    5.70400000000000e-10
    5.80400000000000e-10
    5.90400000000000e-10
    6.00400000000000e-10
    6.10400000000000e-10
    6.20400000000000e-10
    6.30400000000000e-10
    6.40400000000000e-10
    6.50400000000000e-10
    6.60400000000000e-10
    6.70400000000000e-10
    6.80400000000000e-10
    6.90400000000000e-10
    7.00400000000000e-10
    7.10400000000000e-10
    7.20400000000000e-10
    7.30400000000000e-10
    7.40400000000000e-10
    7.50400000000000e-10
    7.60400000000000e-10
    7.70400000000000e-10
    7.80400000000000e-10
    7.90400000000000e-10
    8.00400000000000e-10
    8.10400000000000e-10
    8.20400000000000e-10
    8.30400000000000e-10
    8.40400000000000e-10
    8.50400000000000e-10
    8.60400000000000e-10
    8.70400000000000e-10
    8.80400000000000e-10
    8.90400000000000e-10
    9.00400000000000e-10
    9.10400000000000e-10
    9.20400000000000e-10
    9.30400000000000e-10
    9.40400000000000e-10
    9.50400000000000e-10
    9.60400000000000e-10
    9.70400000000000e-10
    9.80400000000000e-10
    9.90400000000000e-10
    1.00040000000000e-09
    1.01040000000000e-09
    1.02040000000000e-09
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    1.07040000000000e-09
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    1.09040000000000e-09
    1.10040000000000e-09
    1.11040000000000e-09
    1.12040000000000e-09
    1.13040000000000e-09
    1.14040000000000e-09
    1.15040000000000e-09
    1.16040000000000e-09
    1.17040000000000e-09
    1.18040000000000e-09
    1.19040000000000e-09
    1.20040000000000e-09
    1.21040000000000e-09
    1.22040000000000e-09
    1.23040000000000e-09
    1.24040000000000e-09
    1.25040000000000e-09
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    1.30040000000000e-09
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    1.50040000000000e-09
    1.51040000000000e-09
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    1.53040000000000e-09
    1.54040000000000e-09
    1.55040000000000e-09
    1.56040000000000e-09
    1.57040000000000e-09
    1.58040000000000e-09
    1.59040000000000e-09
    1.60040000000000e-09
    1.61040000000000e-09
    1.62040000000000e-09
    1.63040000000000e-09
    1.64040000000000e-09
    1.65040000000000e-09
    1.66040000000000e-09
    1.67040000000000e-09
    1.68040000000000e-09
    1.69040000000000e-09
    1.70040000000000e-09
    1.71040000000000e-09
    1.72040000000000e-09
    1.73040000000000e-09
    1.74040000000000e-09
    1.75040000000000e-09
    1.76040000000000e-09
    1.77040000000000e-09
    1.78040000000000e-09
    1.79040000000000e-09
    1.80040000000000e-09
    1.81040000000000e-09
    1.82040000000000e-09
    1.83040000000000e-09
    1.84040000000000e-09
    1.85040000000000e-09
    1.86040000000000e-09
    1.87040000000000e-09
    1.88040000000000e-09
    1.89040000000000e-09]
y=[-22.8405306447565
-22.2450287793417
-21.6577585104770
-21.0787198381626
-20.5079127623984
-19.9453372831843
-19.3909934005205
-18.8448811144068
-18.3070004248434
-17.7773513318301
-17.2559338353671
-16.7427479354542
-16.2377936320915
-15.7410709252790
-15.2525798150167
-14.7723203013046
-14.3002923841427
-13.8364960635310
-13.3809313394694
-12.9335982119581
-12.4944966809970
-12.0636267465860
-11.6409884087253
-11.2265816674147
-10.8204065226543
-10.4224629744442
-10.0327510227842
-9.65127066767441
-9.27802190911481
-8.91300474710541
-8.55621918164621
-8.20766521273719
-7.86734284037838
-7.53525206456975
-7.21139288531131
-6.89576530260307
-6.58836931644503
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-24.8723362603805
-25.5033422809445
-26.1425798980587
-26.7900491117231]