Noise parameter estimation for non-singleton fuzzy logic systems
Real-world environments face a wide range of noise (uncertainty) sources and gaining insight into the level of noise is a critical part of many applications. While Non-Singleton Fuzzy Logic Systems (NSFLSs), in particular recently introduced advanced variants such as centroid-based NSFLSs have the c...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2018
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| Online Access: | https://eprints.nottingham.ac.uk/53167/ |
| _version_ | 1848798892479479808 |
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| author | Pekaslan, Direnc Garibaldi, Jonathan M. Wagner, Christian |
| author_facet | Pekaslan, Direnc Garibaldi, Jonathan M. Wagner, Christian |
| author_sort | Pekaslan, Direnc |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Real-world environments face a wide range of noise (uncertainty) sources and gaining insight into the level of noise is a critical part of many applications. While Non-Singleton Fuzzy Logic Systems (NSFLSs), in particular recently introduced advanced variants such as centroid-based NSFLSs have the capacity to handle known quantities of uncertainty, thus far, the actual level of uncertainty has had to be defined a priori - i.e. prior to run time of a system or controller. This paper does not focus on such advances within the architecture of NSFLSs, but focuses on a novel two-stage approach for uncertainty handling in fuzzy logic systems which integrates: (i) estimation of noise levels and (ii) the appropriate handling of the noise based on this estimate, by means of a dynamically configured NSFLS. As initial evaluation of the approach, two chaotic nonlinear time series (Mackey-Glass and Lorenz), as well as a real-world Darwin sea level pressure series prediction fuzzy logic systems are implemented and compared to commonly used procedures. The results indicate that the proposed strategy of integrating uncertainty/noise estimation with the capacity of non-singleton fuzzy logic systems has the potential to deliver performance benefits in real-world applications without requiring a priori information on noise levels and thus delivers a first step towards smart, noise-adaptive non-singleton fuzzy logic systems and controllers. |
| first_indexed | 2025-11-14T20:26:59Z |
| format | Conference or Workshop Item |
| id | nottingham-53167 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:26:59Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-531672020-05-04T19:41:14Z https://eprints.nottingham.ac.uk/53167/ Noise parameter estimation for non-singleton fuzzy logic systems Pekaslan, Direnc Garibaldi, Jonathan M. Wagner, Christian Real-world environments face a wide range of noise (uncertainty) sources and gaining insight into the level of noise is a critical part of many applications. While Non-Singleton Fuzzy Logic Systems (NSFLSs), in particular recently introduced advanced variants such as centroid-based NSFLSs have the capacity to handle known quantities of uncertainty, thus far, the actual level of uncertainty has had to be defined a priori - i.e. prior to run time of a system or controller. This paper does not focus on such advances within the architecture of NSFLSs, but focuses on a novel two-stage approach for uncertainty handling in fuzzy logic systems which integrates: (i) estimation of noise levels and (ii) the appropriate handling of the noise based on this estimate, by means of a dynamically configured NSFLS. As initial evaluation of the approach, two chaotic nonlinear time series (Mackey-Glass and Lorenz), as well as a real-world Darwin sea level pressure series prediction fuzzy logic systems are implemented and compared to commonly used procedures. The results indicate that the proposed strategy of integrating uncertainty/noise estimation with the capacity of non-singleton fuzzy logic systems has the potential to deliver performance benefits in real-world applications without requiring a priori information on noise levels and thus delivers a first step towards smart, noise-adaptive non-singleton fuzzy logic systems and controllers. 2018-06-17 Conference or Workshop Item PeerReviewed Pekaslan, Direnc, Garibaldi, Jonathan M. and Wagner, Christian (2018) Noise parameter estimation for non-singleton fuzzy logic systems. In: IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2018), 7-10 October 2018, Miyazaki, Japan. (Submitted) |
| spellingShingle | Pekaslan, Direnc Garibaldi, Jonathan M. Wagner, Christian Noise parameter estimation for non-singleton fuzzy logic systems |
| title | Noise parameter estimation for non-singleton fuzzy logic systems |
| title_full | Noise parameter estimation for non-singleton fuzzy logic systems |
| title_fullStr | Noise parameter estimation for non-singleton fuzzy logic systems |
| title_full_unstemmed | Noise parameter estimation for non-singleton fuzzy logic systems |
| title_short | Noise parameter estimation for non-singleton fuzzy logic systems |
| title_sort | noise parameter estimation for non-singleton fuzzy logic systems |
| url | https://eprints.nottingham.ac.uk/53167/ |