A credibility integration evaluation approach of complex simulation systems based on type-2 fuzzy set and perceptual computing

Credibility evaluation is an important research topic in the simulation field and the credibility integration of complex simulation systems is a difficult problem that needs to be broken through. The existing credibility integration methods can only deal with the deterministic numerical evaluation data, which are described by numbers and intervals. We introduce perceptual computing for the first time to solve the credibility integration problem, and propose a novel credibility integration evaluation approach, which can deal with the evaluation data containing both numerical and linguistical descriptions. Firstly, we propose the credibility transformation approach and the weight transformation approach to map the evaluation data into interval type-2 fuzzy sets. Then, the crdibility integration perceptual computer with perceptual computer as the prototype is proposed to aggregate the indicators and the credibility label is generated. Finally, experiments are presented to demonstrate the effectiveness and performance of the proposed approach.