Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction
In this paper, our aim is to compare and contrast various ways of modeling uncertainty by using different type-2 fuzzy membership functions available in literature. In particular we focus on a novel type-2 fuzzy membership function–”Elliptic membership function”. After briefly explaining the motivat...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
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2017
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| Online Access: | https://eprints.nottingham.ac.uk/45241/ |
| _version_ | 1848797095530594304 |
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| author | Kayacan, Erdal Coupland, Simon John, Robert Khanesar, Mojtaba Ahmadieh |
| author_facet | Kayacan, Erdal Coupland, Simon John, Robert Khanesar, Mojtaba Ahmadieh |
| author_sort | Kayacan, Erdal |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In this paper, our aim is to compare and contrast various ways of modeling uncertainty by using different type-2 fuzzy membership functions available in literature. In particular we focus on a novel type-2 fuzzy membership function–”Elliptic membership function”. After briefly explaining the motivation behind the suggestion of the elliptic membership function, we analyse the uncertainty distribution along its support, and we compare its uncertainty modeling capability with the existing membership functions. We also show how the elliptic membership functions perform in fuzzy arithmetic. In addition to its extra advantages over the existing type-2 fuzzy membership functions such as having decoupled parameters for its support and width, this novel membership function has some similar features to the Gaussian and triangular membership functions in addition and multiplication operations. Finally, we have tested the prediction capability of elliptic membership functions using interval type-2 fuzzy logic systems on US Dollar/Euro exchange rate prediction problem. Throughout the simulation studies, an extreme learning machine is used to train the interval type-2 fuzzy logic system. The prediction results show that, in addition to their various advantages mentioned above, elliptic membership functions have comparable prediction results when compared to Gaussian and triangular membership functions. |
| first_indexed | 2025-11-14T19:58:26Z |
| format | Conference or Workshop Item |
| id | nottingham-45241 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:58:26Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-452412020-05-04T18:54:45Z https://eprints.nottingham.ac.uk/45241/ Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction Kayacan, Erdal Coupland, Simon John, Robert Khanesar, Mojtaba Ahmadieh In this paper, our aim is to compare and contrast various ways of modeling uncertainty by using different type-2 fuzzy membership functions available in literature. In particular we focus on a novel type-2 fuzzy membership function–”Elliptic membership function”. After briefly explaining the motivation behind the suggestion of the elliptic membership function, we analyse the uncertainty distribution along its support, and we compare its uncertainty modeling capability with the existing membership functions. We also show how the elliptic membership functions perform in fuzzy arithmetic. In addition to its extra advantages over the existing type-2 fuzzy membership functions such as having decoupled parameters for its support and width, this novel membership function has some similar features to the Gaussian and triangular membership functions in addition and multiplication operations. Finally, we have tested the prediction capability of elliptic membership functions using interval type-2 fuzzy logic systems on US Dollar/Euro exchange rate prediction problem. Throughout the simulation studies, an extreme learning machine is used to train the interval type-2 fuzzy logic system. The prediction results show that, in addition to their various advantages mentioned above, elliptic membership functions have comparable prediction results when compared to Gaussian and triangular membership functions. 2017-07-09 Conference or Workshop Item PeerReviewed Kayacan, Erdal, Coupland, Simon, John, Robert and Khanesar, Mojtaba Ahmadieh (2017) Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction. In: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 9-12 July 2017, Naples, Italy. Elliptic membership function type-2 fuzzy logic theory uncertainty fuzzy sets Gaussian triangular time series prediction http://ieeexplore.ieee.org/abstract/document/8015457/ 10.1109/FUZZ-IEEE.2017.8015457 10.1109/FUZZ-IEEE.2017.8015457 10.1109/FUZZ-IEEE.2017.8015457 |
| spellingShingle | Elliptic membership function type-2 fuzzy logic theory uncertainty fuzzy sets Gaussian triangular time series prediction Kayacan, Erdal Coupland, Simon John, Robert Khanesar, Mojtaba Ahmadieh Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction |
| title | Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction |
| title_full | Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction |
| title_fullStr | Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction |
| title_full_unstemmed | Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction |
| title_short | Elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction |
| title_sort | elliptic membership functions and the modeling uncertainty in type-2 fuzzy logic systems as applied to time series prediction |
| topic | Elliptic membership function type-2 fuzzy logic theory uncertainty fuzzy sets Gaussian triangular time series prediction |
| url | https://eprints.nottingham.ac.uk/45241/ https://eprints.nottingham.ac.uk/45241/ https://eprints.nottingham.ac.uk/45241/ |