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feifei_ney木蟲 (小有名氣)
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[求助]
用Matlab求解方程
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有個遷移模型方程 已知MF,∞=9.18mg,Lp=0.009, MF,t與t的一組相關(guān)實驗數(shù)據(jù)如下所示 t MF,t 7200 3.28265 86400 5.57149 345600 6.84803 864000 7.47618 7.776E6 9.17744 想求解得到D值。 請大家?guī)兔η蠼庖幌,不勝感激,希望能夠提供詳?xì)的求解步驟。 |
木蟲 (小有名氣)
木蟲 (小有名氣)
榮譽(yù)版主 (著名寫手)
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專家經(jīng)驗: +4 |
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用最小二乘法解了下 不知道你看結(jié)果如何 整個文件復(fù)制到editor中保存為m文件后運(yùn)行 D0區(qū)不同初值的結(jié)果 D0=3.55e-15 s = 0.9462 0.3616 0.0000 0.0000 0 s = 0 0 0 0 0 Initial point is a local minimum. Optimization completed because the size of the gradient at the initial point is less than the default value of the function tolerance. D = 3.5500e-015 resnorm = 0.0370 residual = 0.1923 exitflag = 1 output = firstorderopt: 2.1708e-008 iterations: 0 funcCount: 2 cgiterations: 0 algorithm: 'large-scale: trust-region reflective Newton' message: [1x500 char] lambda = lower: 6.1148e+006 upper: 0 D0=3.55e-19 s = 0.9995 0.9935 0.9742 0.9355 0.4218 s = 0 0 0 0 0 s = 0 0 0 0 0 s = 0 0 0 0 0 Local minimum found. Optimization completed because the size of the gradient is less than the default value of the function tolerance. D = 2.4089e-008 resnorm = 0.4438 residual = 0.6662 exitflag = 1 output = firstorderopt: 0 iterations: 1 funcCount: 4 cgiterations: 0 algorithm: 'large-scale: trust-region reflective Newton' message: [1x427 char] lambda = lower: 0 upper: 0 jacobian = All zero sparse: 1-by-1 |

榮譽(yù)版主 (著名寫手)
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專家經(jīng)驗: +4 |

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