Title :
Real Time Model of Fuzzy Random Regression Based on a Convex Hull Approach
Author :
Ramli, Azizul Azhar ; Watada, Junzo ; Pedrycz, Witold
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan
Abstract :
In this study, we present a new idea dealing with the analysis of fuzzy random variables (FRVs) being treated as samples of data. The proposed concept can be used to model various real-life situations where uncertainty is not only present in the form of randomness but also comes in the form of imprecision described in terms of fuzzy sets. We propose a hybrid approach, which combines a convex hull approach (called Beneath-Beyond algorithm) with a fuzzy random regression analysis. Falling under the umbrella of intelligent data analysis (IDA) tool, this approach is suitable for real-time implementation of data analysis. For a fuzzy random data set, we include simulation results and highlight two main advantages, namely a decrease of required analysis time and a reduction of computational complexity. This emphasizes that the proposed IDA approach becomes an efficient way for real-time data analysis.
Keywords :
data analysis; fuzzy set theory; random processes; regression analysis; IDA tool; beneath-beyond algorithm; computational complexity; convex hull approach; data sampling; fuzzy random regression; fuzzy random variable; fuzzy set; intelligent data analysis; real time model; Algorithm design and analysis; Analytical models; Biological system modeling; Computational modeling; Data analysis; Real time systems; Regression analysis; convex hull; fuzzy random regression; fuzzy random variables; intelligent data analysis;
Conference_Titel :
Advances in Computing, Control and Telecommunication Technologies (ACT), 2010 Second International Conference on
Conference_Location :
Jakarta
Print_ISBN :
978-1-4244-8746-2
Electronic_ISBN :
978-0-7695-4269-0
DOI :
10.1109/ACT.2010.19