Abstract
Comprehensive and objective credibility assessments of complex simulation models are crucial to the successful application of models and simulation results in various critical evaluation and decision making problems. However, the credibility assessment of a complex simulation model usually encounters many challenges, involves the measurements and evaluations of hundreds of qualitative and quantitative indicators, and requires the integration of heterogeneous results. Therefore, cloud models which can describe both fuzziness and randomness are adopted to represent and aggregate diverse evaluation results of various qualitative and quantitative indicators. Then, crisp values, interval numbers, statistical data and linguistic terms can all be represented and aggregated by normal cloud models. The main advantages of our methods are that diverse evaluation results of various indicators can be represented and aggregated, and uncertainties associated with these results of leaf indicators can be preserved and propagated into the final assessment result. A missile simulation model credibility assessment example is presented to illustrate the proposed methods.
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Acknowledgment
This work was supported by the Equipment Pre-Research Project of the ‘Thirteenth Five-Year-Plan’ of China under Grant 6140001010506.
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Yang, X., Xu, Z., He, R., Xue, F. (2019). Credibility Assessment of Complex Simulation Models Using Cloud Models to Represent and Aggregate Diverse Evaluation Results. In: Huang, DS., Huang, ZK., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2019. Lecture Notes in Computer Science(), vol 11645. Springer, Cham. https://doi.org/10.1007/978-3-030-26766-7_28
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DOI: https://doi.org/10.1007/978-3-030-26766-7_28
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