Before revision:  Here}  , we use instead approximate Bayesian computation (ABC) to calibrate the parameters in a data-driven automatic manner. ABC requires a prior distribution for the parameters, which we take to be uniform over a known range of plausible parameter values. ABC requires the generation of many pseudo-data by expensive simulation runs, we have thus developed an high performance computing (HPC) ABC framework , taking into account accuracy and scalability.
After revision:  Here} , we use instead approximate Bayesian computation (ABC) to calibrate the parameters in a data-driven manner. As ABC requires the generation of many pseudo-data by expensive simulation runs, we have thus developed an high performance computing (HPC) ABC framework , taking into account accuracy and scalability.