1. Parameter identification technology is a technology that combines theoretical models with experimental data for prediction . Parameter identification determines a set of model parameters based on the experimental data and the established model , so that the numerical results calculated by the model can best fit the test data (which can be regarded as a curve fitting problem), so that the unknown process can be Make predictions and provide some theoretical guidance.
2. In the specific research, first establish a rough model, and use this model to predict the test measurement results. When the error between the calculated numerical results and the test values is large, it is considered that the mathematical model does not match the actual process. Or the gap is large, and then the model is modified, and the modification is selected again. When the predicted results are consistent with the measured results, the model is considered to have high credibility.