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A comparative experimental evaluation on performance of type-1 and interval type-2 Takagi-Sugeno fuzzy models

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Abstract

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.

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (Nos. 61772002, 61976245), the Fundamental Research Funds for the Central Universities (Nos. XDJK2019B029, SWU119045, SWU119063, SWU119043)

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Authors and Affiliations

  1. School of Mathematics and Statistics, Southwest University, Chongqing, 400715, People’s Republic of China

    Kehua Yuan & Tao Zhan

  2. College of Artificial Intelligence, Southwest University, Chongqing, 400715, People’s Republic of China

    Wentao Li, Weihua Xu & Libo Zhang

  3. School of Automation, Beijing Institute of Technology, Beijing, 100081, People’s Republic of China

    Shuai Liu

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  1. Kehua Yuan
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  2. Wentao Li
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Correspondence to Wentao Li.

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Yuan, K., Li, W., Xu, W. et al. A comparative experimental evaluation on performance of type-1 and interval type-2 Takagi-Sugeno fuzzy models. Int. J. Mach. Learn. & Cyber. 12, 2135–2150 (2021). https://doi.org/10.1007/s13042-021-01298-5

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