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Sensitivity Analysis of GreenLab Model for Maize

机译:玉米GreenLab模型的敏感性分析。

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摘要

Sensitivity analysis is a powerful tool which gives important insights regarding parameterization in the process of model design. For an empirical model like the Greenlab model of plant growth relying on parameter estimation from experimental data, such study should open new perspectives for model identification. This study was aimed at analyzing the sensitivity of GreenLab model for maize. When the value of biomass production is considered as the output, the system tends to be linear, the level is above 94% for the SRC (Standardized Regression coefficients) study. Conversion efficiency and characteristic surface are proved to be the most sensitive factors. In Sobol's measure, we excluded the two most sensitive factors in the analysis, then the system linearity is weaker. We obtained the detailed sensitivity indexes for the other uncertain parameters, by which we get the driving forces of maize growth at different stages.
机译:灵敏度分析是一个功能强大的工具,可为模型设计过程中的参数化提供重要的见解。对于依赖于实验数据参数估计的经验模型(如Greenlab植物生长模型),此类研究应为模型识别打开新的视野。这项研究旨在分析GreenLab模型对玉米的敏感性。当将生物量生产的价值视为输出时,系统趋于线性,对于SRC(标准回归系数)研究,该水平高于94%。转换效率和特征表面被证明是最敏感的因素。在Sobol的度量中,我们在分析中排除了两个最敏感的因素,因此系统线性度较弱。我们获得了其他不确定参数的详细灵敏度指标,从而获得了不同阶段玉米生长的驱动力。

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