考虑相关性的多元输出仿真模型验证方法

Complex simulation models often generate the multivariate and different types of output, some problems such as the lacking variables information and the inaccuracy correlation measurement are involved in the existing validation methods. A novel validation method combining variables selection with area metric is proposed, the multiple outputs with correlation are selected for the associated validation under uncertainty. The fractal dimension and mutual information methods are primarily applied to analyze the correlation among multivariate and divise responses and extract the correlated variable subsets. Next, the interesting data characteristics of all variables are extracted in subset and the corresponding joint cumulative distribution function (JCDF) of each subset related to any characteristic is calculated. The area metric is used to measure the difference between the simulation and reference output JCDFs of multivariate characteristics in each subset, and the differences are transformed into the consistency degrees. Then the multiple validation results are integrated to obtain the model credibility. Finally, the method is validated through the application case and comparison experiments.