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首页> 外文期刊>Mathematical Biosciences: An International Journal >Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations
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Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations

机译:在非线性ODE模型中找到可识别的参数组合及其输入输出方程的合理重新参数化

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When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gr?bner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel.
机译:在检查动态系统模型的结构可识别性时,某些参数可以取无穷多个值,但仍会产生相同的输入输出数据。这些参数和模型被认为是无法识别的。查找参数的可识别组合以重新参数化模型,为定量分析模型和根据组合计算解决方案提供了一种方法。在本文中,我们将回顾和探索使用Gr?bner Bases查找可识别参数组合的算法的性质,并证明这些参数组合的有用的理论性质。我们证明了使用该算法可以找到一组M个代数无关的可识别参数组合,并且在这些参数组合上存在唯一的输入-输出方程式有理重新参数化。我们还演示了该程序在非线性生物模型中的应用。

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