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 architectures of fuzzy models are involved in the comparative studies presented here: (1) fuzzy clustering method-based Takagi-Sugeno (TS) fuzzy models (Fuzzy C-Means based type-1, Fuzzy C-Means based interval type-2); (2) static TS-based fuzzy models (static type-1, A2C0, A2C1, EKFT2 and their associated type-1 models) and (3) evolving TS fuzzy models (SEIT2 and its associated type-1 counterpart, SCIT2 and its associated type-1 model). The experiments are carried out by involving 15 publicly available datasets. The accuracy of these two types of fuzzy models is assessed vis-a-vis their development time. Testing is involved to evaluate whether there are statistically significant differences between the performance of the type-2 and type-1 fuzzy models.

在文献中，有大量研究通过实验证明了2型模糊模型的性能优于1型模糊模型。尽管这些模型的优点似乎是合理的，但在现有研究中并未仔细评估和严格评估改进的量化。仍然缺乏对类型2模糊模型的收益进行全面的多目标实验数值评估。在这项研究中，根据准确性和计算开销的标准对类型1和类型2模糊模型的性能进行了数值评估，从而对这两个性能指标之间的现有折衷进行了全面分析。 。在拟议的数字评估中，针对类型2模糊模型及其关联的类型1对应模型（类型2关联的类型1模型共享相似的结构和相同的开发方法）进行评估。此处介绍的比较研究涉及模糊模型的三种体系结构：（1）基于模糊聚类方法的Takagi-Sugeno（TS）模糊模型（基于模糊C均值1型，基于模糊C均值间隔2型） ; （2）基于静态TS的模糊模型（静态type-1，A2C0，A2C1，EKFT2及其关联的type-1模型）和（3）演进的TS模糊模型（SEIT2及其关联的type-1对应物，SCIT2及其关联的1型模型）。通过涉及15个公开可用的数据集来进行实验。相对于它们的开发时间评估了这两种类型的模糊模型的准确性。