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对番茄生长模型参数进行准确估算是模型得以验证和面向应用的前提条件。基于番茄拓扑结构,采用非线性最小二乘优化方法,通过对植株形态数据的多目标拟合,实现模型参数的最优估计和校准。非线性最小二乘法的权值根据目标数据自动调整,使得不同量纲和不同数值范围的观测数据可以在同一水平上进行,提高了计算的精度和稳定性;另一方面用差商近似代替导数加快了算法的收敛速度。通过应用拟合优度检验,得出模型输出对观测值的拟合程度较好,说明模型合理,参数可靠。实践表明该估算方法是对模型进行验证的一个行之有效的方法。
Accurate estimation of tomato growth model parameters is a prerequisite for the validation and application of the model. Based on the tomato topological structure, a non-linear least-squares optimization method was used to achieve the optimal estimation and calibration of the model parameters through the multi-objective fitting of the plant morphology data. The weight of the nonlinear least squares method is automatically adjusted according to the target data so that the observation data of different dimensions and different numerical ranges can be carried out at the same level, which improves the accuracy and stability of the calculation. On the other hand, Speed up the convergence of the algorithm. Through the application of the goodness of fit test, it is concluded that the fitting degree of the model output to the observed value is good, indicating that the model is reasonable and the parameters are reliable. Practice shows that the estimation method is an effective method to validate the model.