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OPTIMAL FITTING PARAMETER DETERMINING METHOD AND DEVICE, AND OPTIMAL FITTING PARAMETER DETERMINING PROGRAM

机译:最佳拟合参数确定方法和装置,以及最佳拟合参数确定程序

摘要

The fitting parameters of a physics model are represented in the form of real-number vectors as the information on chromosomes of a genetic algorithm, a plurality of individuals having the chromosomes is prepared and a genetic algorithm is used to fit and optimize the parameters to the measured data points of physical quantities. Child individuals from the crossover process of the genetic algorithm are generated from three parent individuals at a determined normal distribution probability, and the replacement process takes individuals that are superior with respect to all criteria from among the selected parent individuals and plurality of child individuals and makes them the individuals of the next generation population. Moreover, optimal fitting parameters are found for each set of measurement data points under a plurality of experimental conditions, and collective fitting is performed so that the fitting parameters vary smoothly even among experimental conditions: Thereby, it is possible to simulate physical phenomena with physics models without error even under experimental conditions at which experiments were not performed.
机译:物理模型的拟合参数以实数矢量的形式表示,作为遗传算法的染色体信息,准备了多个具有该染色体的个体,并使用遗传算法对参数进行拟合和优化。实物测量数据点。来自遗传算法交叉过程的儿童个体是由三个父母个体以确定的正态分布概率生成的,替换过程从选定的父母个体和多个孩子个体中挑选出在所有标准方面均优于其的个体,他们是下一代人口的个体。此外,在多个实验条件下为每组测量数据点找到最佳拟合参数,并执行集体拟合,以使拟合参数即使在实验条件之间也能平稳变化:从而可以用物理模型模拟物理现象即使在没有进行实验的实验条件下也不会出错。

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