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In the literature, there have been numerous studies demonstrating experimentally that type-2 fuzzy models outperform their type-1 counterparts. Although the advantages of these models seem to be well justified, the quantification of the improvements is not carefully evaluated and critically assessed in the existing studies. A thorough multi-objective experimental numeric evaluation of benefits of type-2 fuzzy models is still lacking. In this study, a numeric evaluation of the performance of type-1 and type-2 fuzzy models is carried out in terms of the criteria of accuracy and computing overhead, which leads to a thorough analysis of existing trade-offs between these two performance indexes. In the proposed numeric evaluation, type-2 fuzzy models are evaluated against their associated type-1 counterparts (the type-2 associated type-1 models sharing similar structure and the same development method). Three …