Multi-source data fusion evaluation method based on uncertainty quantification and Bayes method for success-failure type test

Jiajia Wang; Jingyuan He; Jing Ma

doi:10.1117/12.2667695

28 March 2023 Multi-source data fusion evaluation method based on uncertainty quantification and Bayes method for success-failure type test

Jiajia Wang, Jingyuan He, Jing Ma

Author Affiliations +

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125661N (2023) https://doi.org/10.1117/12.2667695
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

In this paper, we use Uncertainty Quantification method to analyze the data from three types of success-failure type test sources: physical test, semi-physical test and computer simulation test. Bayes method is used to evaluate the data fusion of multiple source test, and the validity and applicability of the method are verified by experiments.

Citation Download Citation

Jiajia Wang, Jingyuan He, and Jing Ma "Multi-source data fusion evaluation method based on uncertainty quantification and Bayes method for success-failure type test", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125661N (28 March 2023); https://doi.org/10.1117/12.2667695

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