论文标题
通过降低非可识别性，在ODE模型中更有效的可识别性验证
More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability
论文作者
论文摘要
结构性全局参数可识别性指示是否可以在没有噪声的情况下从给定的输入和输出中确定参数的值。如果给定模型的参数可能存在无限的值，则此类参数称为不可识别。我们提出了一个程序，通过消除代数独立的不可识别参数来加速全局可识别性查询。我们提出的方法可大大提高不同计算机代数框架的性能。
Structural global parameter identifiability indicates whether one can determine a parameter's value from given inputs and outputs in the absence of noise. If a given model has parameters for which there may be infinitely many values, such parameters are called non-identifiable. We present a procedure for accelerating a global identifiability query by eliminating algebraically independent non-identifiable parameters. Our proposed approach significantly improves performance across different computer algebra frameworks.
