Reducing Computational Overhead by Improving the CRI and IRI Implication Step
Keyword(s):
In conventional SISO fuzzy expert systems (n-element input,m-element output), the implication step requires theO(n×m)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 toO((n+m)log2(n+m)). 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.
1997 ◽
Vol 39
(9)
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pp. 607-616
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2012 ◽
Vol 52
(No. 4)
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pp. 187-196
1995 ◽
Vol 9
(1)
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pp. 3-14
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2020 ◽
Vol 6
(4 (108))
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pp. 22-31