Abstract:

To address the validation and ranking evaluation of simulation models whose output are non-stationary and fast variational, a ranking evaluation method based on Hilbert-Huang transform is presented. The simulation output and experimental observations with the nonstationary and fast variational data are decomposed into trend items and stationary items respectively. The consistency of trend items is analyzed by comparing the difference in distance and shape and the agreement extent of stationary items is obtained by means of the power spectral density analysis based on Hilbert transform. For satisfying the condition of spectral analysis, the smoothing sample spectral density of stationary items based on Hilbert transform is demonstrated to obey the chi-square distribution. Next the three consistency results are integrated depending on grey relational analysis to accomplish ranking evaluation of simulation models. Finally, the effectiveness of this method is verified by an example.