Parameter identification is the process of determining unknown model parameters by fitting the model to observed data, ensuring the best match between predictions and measurements. It involves optimization techniques to minimize the discrepancy between the model’s outputs and the experimental or real-world data, often under constraints to ensure parameter plausibility.