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A combination of genetic algorithm-based fuzzy c-means with a convex hull-based regression for real-time fuzzy switching regression analysis: application to industrial intelligent data analysis

Ramli, Azizul Azhar and Watada, Junzo and Pedrycz, Witold (2014) A combination of genetic algorithm-based fuzzy c-means with a convex hull-based regression for real-time fuzzy switching regression analysis: application to industrial intelligent data analysis. IEEJ Transactions on Electrical and Electronic Engineering, 9 (1). pp. 71-82. ISSN 1931-4981

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Abstract

Processing an increasing volume of data, especially in industrial and manufacturing domains, calls for advanced tools of data analysis. Knowledge discovery is a process of analyzing data from different perspectives and summarizing the results into some useful and transparent findings. To address such challenges, a thorough extension and generalization of well-known techniques such as regression analysis becomes essential and highly advantageous. In this paper, we extend the concept of regression models so that they can handle hybrid data coming from various sources which quite often exhibit diverse levels of data quality. The major objective of this study is to develop a sound vehicle of a hybrid data analysis, which helps in reducing the computing time, especially in cases of real-time data processing. We propose an efficient real-time fuzzy switching regression analysis based on a genetic algorithm-based fuzzy C-means associated with a convex hull-based fuzzy regression approach. The method enables us to deal with situations when one has to deal with heterogeneous data which were derived from various database sources (distributed databases). In the proposed design, we emphasize a pivotal role of the convex hull approach, which is essential to alleviate the limitations of linear programming when being used in modeling of real-time systems. O 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Item Type: Article
Uncontrolled Keywords: convex hull; fuzzy switching regression; genetic algorithm; heterogeneous data; intelligent data analysis; steam generator
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 01 Jun 2014 04:20
Last Modified: 21 Jan 2015 08:27
URI: http://eprints.uthm.edu.my/id/eprint/5272
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