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Constructing Interval Type-2 Fuzzy Systems (IT2FS) with Memetic Algorithm: Elucidating Performance with Noisy Data

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International Conference on Innovative Computing and Communications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 473))

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Abstract

Fuzzy modeling is a challenging task and becomes more complex when designing T2FS, which requires identification of more parameters as compared to T1FS. The problem of fuzzy modeling can be expressed as a high-dimensional search and optimization process, and EAs have the ability to search for optimal solutions in high-dimensional search space, so researchers used various EAs for fuzzy modeling. GAs are widely used for finding solutions in large search spaces, and MAs have characteristics of both global and local optimizations. This paper describes how to use MAs and GAs to identify IT2FS, including how to build MFs for both input and output, as well as how to generate a rule base from a data collection. The efficiency of T1FS and IT2FS for noisy data is also compared with GAs and MAs in the paper. For comparison, we consider four different problems: a rapid Ni–Cd battery charger, data from Box and Jenkins’s gas furnace, and the iris and wine classification datasets. In the presence of noise, the results imply that IT2FS is more efficient than T1FS, and MAs are more efficient than GAs.

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Author information

Authors and Affiliations

  1. MMICTBM (MCA), MMDU, Mullana, Ambala, Haryana, India

    Savita Wadhawan

  2. Department of Computer Science and Engineering, Punjabi University, Patiala, Punjab, India

    Savita Wadhawan

  3. IIT Mandi iHUB and HCI Foundation, Mandi, Himachal Pradesh, India

    Arvind K. Sharma

  4. Department of Computer Science & Engineering, University School of Engineering & Technology, Rayat Bahra University, Mohali, Punjab, India

    Arvind K. Sharma

Authors
  1. Savita Wadhawan
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  2. Arvind K. Sharma
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Corresponding author

Correspondence to Savita Wadhawan .

Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  2. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Ashish Khanna

  3. Rajnagar Mahavidyalaya, Birbhum, West Bengal, India

    Siddhartha Bhattacharyya

  4. Department of Information Technology, Cairo University, Giza Governorate, Egypt

    Aboul Ella Hassanien

  5. Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India

    Sameer Anand

  6. Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India

    Ajay Jaiswal

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Wadhawan, S., Sharma, A.K. (2023). Constructing Interval Type-2 Fuzzy Systems (IT2FS) with Memetic Algorithm: Elucidating Performance with Noisy Data. In: Gupta, D., Khanna, A., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 473. Springer, Singapore. https://doi.org/10.1007/978-981-19-2821-5_1

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  • DOI: https://doi.org/10.1007/978-981-19-2821-5_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-2820-8

  • Online ISBN: 978-981-19-2821-5

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