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OwnerMasahiro Murakawa, Tetsuya Higuchiinventors
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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.
A method of determining optimal fitting parameters, comprising:
An optimal fitting parameter determination apparatus for a physics model having a plurality of parameters, comprising:
An optimal fitting parameter determination program executed by a computer, that implements a process wherein:
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