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Similarity Measures Between Type-2 Fuzzy Sets

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Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1088))

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Abstract

As an indispensable parameter in type 2 fuzzy logic, the similarity measure has a favorable application prospect. In this paper, the research history and status of this index are discussed briefly. Several typical definitions widely concerned by scholars are researched as emphases, including similarity measures of interval type-2 fuzzy sets and those of ordinary type-2 fuzzy sets. Several successful application cases in the fields of pattern recognition, fuzzy clustering, simplification of fuzzy rule base in recent years are listed, and a simulation case of short term power load forecasting is presented to verify the performance of a similarity measure between interval type-2 fuzzy sets. Finally, the deficiency at present and the future development trend are pointed out.

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Acknowledgements

This work was supported by Teaching Quality and Teaching Reform Project of Department of Education of Guangdong Province (Grant No. 2017009), Innovative Capacity Development Project of Zhuhai College of Jilin University (project number: 2018XJCQ022), Innovative Entrepreneurship Education Curriculum Development Project of Zhuhai College of Jilin University, Teacher Education Development Fund Project of Zhuhai College of Jilin University (project number: JZ2018JZA11), Teaching Quality Engineering Construction Project of Zhuhai College of Jilin University in 2019, Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education.

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Authors and Affiliations

  1. School of Computer, Zhuhai College of Jilin University, Zhuhai, 519041, Guangdong, China

    Jing Wang

  2. Department of Electromechanical Management, China Coast Guard Academy, Ningbo, 315801, Zhejiang, China

    Gao Zheng

Authors
  1. Jing Wang
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  2. Gao Zheng
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Correspondence to Jing Wang .

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Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Chuanchao Huang

  2. Computer Science and Information Management, Providence University, Taichung, Taiwan

    Yu-Wei Chan

  3. University of Aizu, Fukushima, Japan

    Neil Yen

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Wang, J., Zheng, G. (2020). Similarity Measures Between Type-2 Fuzzy Sets. In: Huang, C., Chan, YW., Yen, N. (eds) Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019). Advances in Intelligent Systems and Computing, vol 1088. Springer, Singapore. https://doi.org/10.1007/978-981-15-1468-5_50

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