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Fuzzy Logic and Neuro-Fuzzy Modeling

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IJCA Proceedings on National Conference on Recent Trends in Computing
© 2012 by IJCA Journal
NCRTC - Number 4
Year of Publication: 2012
Authors:
S. R. Nikam
P. J. Nikumbh
S. P. Kulkarni

S R Nikam, P J Nikumbh and S P Kulkarni. Article: Fuzzy Logic and Neuro-Fuzzy Modeling. IJCA Proceedings on National Conference on Recent Trends in Computing NCRTC(4):22-31, May 2012. Full text available. BibTeX

@article{key:article,
	author = {S. R. Nikam and P. J. Nikumbh and S. P. Kulkarni},
	title = {Article: Fuzzy Logic and Neuro-Fuzzy Modeling},
	journal = {IJCA Proceedings on National Conference on Recent Trends in Computing},
	year = {2012},
	volume = {NCRTC},
	number = {4},
	pages = {22-31},
	month = {May},
	note = {Full text available}
}

Abstract

Fuzzy logic and fuzzy systems have recently been receiving a lot of attention; both from the media and scientific community, yet the basic techniques were originally developed in the mid-sixties. Fuzzy logic provides a formalism for implementing expert or heuristic rules on computers, and while this is the main goal in the field of expert or knowledge-based systems, fuzzy systems have had considerably more success and have been sold in automobiles, cameras, washing machines, rice cookers, etc. This report will describe the theory behind basic fuzzy logic and investigate how fuzzy systems work. This leads naturally on to neuro fuzzy systems which attempt to fuse the best points of neural and fuzzy networks into a single system. Throughout this report, the potential limitations of this method will be described as this provides the reader with a greater understanding of how the techniques can be applied.

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