... to the evolutionary algorithm. The essence of Bayesian optimization is to strategically select the next set of parameters for evaluation by first constructing a surrogate model to learn the response surface of the objective function. However, for the problem of model calibration, the theoretical analysis in Refs...

... data from multiple components at different time instants and spatial locations. The availability of data for model calibration is typically sparse in realistic systems, and data might be collected at different time instances for different system components. When multiple models are used to describe...