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A real-time analysis of granular information: some initial thoughts on a convex hull-based regression

Ramli, Azizul Azhar and Witold Pedrycz, Witold Pedrycz and Junzo Watada, Junzo Watada and Arbaiy, Nureize A real-time analysis of granular information: some initial thoughts on a convex hull-based regression. In: The 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 27-30 June 2011, Taipei, Taiwan.

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Regression models are well known and widely used as one of the important categories of models in system modeling. In this paper, we extend the concept of fuzzy regression in order to handle real-time implementation of data analysis of information granules. An ultimate objective of this study is to develop a hybrid of a genetically-guided clustering algorithm called genetic algorithm-Fuzzy C-Means (GA-FCM) and a convex hull-based fuzzy regression being regarded as a potential solution to the formation of information granules. It is anticipated that the setting of Granular Computing will help us reduce the computing time, especially in case of real-time data analysis, as well as an overall computational complexity. We propose an efficient real-time granular fuzzy regression analysis based on convex hull approach in which a Beneath-Beyond algorithm is employed to design a convex hull. In the proposed design setting, we emphasized a pivotal role of the convex hull approach, which becomes crucial in alleviating limitations of linear programming manifest in system modeling.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: convex hull; fuzzy regression; Fuzzy C-Means; genetic algorithm; granular computing
Subjects: Q Science > QA Mathematics > QA273 Probabilities. Mathematical statistics
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 18 Jan 2013 03:54
Last Modified: 21 Jan 2015 07:52
URI: http://eprints.uthm.edu.my/id/eprint/2948
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