Loading [MathJax]/extensions/TeX/upgreek.js
ACPOP: Ambiguity correction-based pseudo-outer-product fuzzy rule identification algorithm | IEEE Conference Publication | IEEE Xplore

ACPOP: Ambiguity correction-based pseudo-outer-product fuzzy rule identification algorithm


Abstract:

Fuzzy rules generated from neuro-fuzzy systems may contain ambiguous rules, due to numerous factors. While contradiction-correction often ensures consistency in fuzzy rul...Show More

Abstract:

Fuzzy rules generated from neuro-fuzzy systems may contain ambiguous rules, due to numerous factors. While contradiction-correction often ensures consistency in fuzzy rule-bases, a differing approach should be reserved for problems where the linguistic definitions can be mutually-inclusive. For these cases, the proposed ambiguity-correction approach is a simple procedure that prevents excessive skew towards stronger rules, and still creates consistent fuzzy rule-base. This paper describes a proof-of-concept model, ACPOP-CRI(S), where ambiguity-correction can be adapted to the generic POP-CRI(S) framework. Experimental results on the Nakanishi dataset shows that the ACPOP rule identification algorithm has the potential to perform better, and generate fewer rules than the generic POP algorithm.
Date of Conference: 20-24 August 2009
Date Added to IEEE Xplore: 02 October 2009
ISBN Information:
Print ISSN: 1098-7584
Conference Location: Jeju, Korea (South)

References

References is not available for this document.