Mixed moment validation metric for models with multivariate output

Lufeng Zhao, Zhenzhou Lyu, Leigang Zhang, Xinwei Wang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Considering the relations among multi-outputs and the mean of single output, the mathematical expectation of single dimensional variable and covariance metric of multi-dimensional variables were introduced into the validation metrics for models. The new metrics of LA-3M and LR-3M were proposed for validating multi-responses at a single validation site, while the metrics of GA-3M and GR-3M were proposed to collect data of multiple responses observed at multiple validation sites. These metrics were examined through a numerical test case and an engineering example to illustrate their feasibility and effectiveness. Results show that the proposed metrics are efficient and they can easily measure the differential degree of multiple responses between calculation model and physical experiment.

Original languageEnglish
Pages (from-to)61-68
Number of pages8
JournalGuofang Keji Daxue Xuebao/Journal of National University of Defense Technology
Volume37
Issue number6
DOIs
StatePublished - 28 Dec 2015

Keywords

  • Correlation
  • Mixed moment
  • Model validation
  • Models with multivariate output
  • Uncertainty

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