Reducing Computational Overhead by Improving the CRI and IRI Implication StepReport as inadecuate




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Journal of Control Science and Engineering - Volume 2015 2015, Article ID 725258, 10 pages -

Research ArticleDepartment of Electrical Engineering, Dayeh University, No. 168, University Road, Changhua 51591, Taiwan

Received 18 December 2014; Accepted 5 March 2015

Academic Editor: Lifeng Ma

Copyright © 2015 Thoai Phu Vo and Joy Iong-Zong Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In conventional SISO fuzzy expert systems -element input -element output, the implication step requires the operations using compositional rule-based inference CRI and individual rule-based inference IRI. However, this introduces excessive complexity. This paper proposes two methods, sort compositional rule-based inference SCRI and sort individual rule-based inference SIRI aiming at reducing both temporal and spatial complexity by changing the operation of the implication step to log2. We also propose a divide-and-conquer technique, called Quicksort, to verify the accuracy of SCRI and SIRI algorithms deployment to easily outperform the CRI and IRI methods.





Author: Thoai Phu Vo and Joy Iong-Zong Chen

Source: https://www.hindawi.com/



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