ENCODING FUZZY DIAGNOSIS RULES AS OPTIMISATION PROBLEMS

Antonio Sala, Alicia Esparza, Carlos Ariño, Jose V. Roig

Abstract

This paper discusses how to encode fuzzy knowledge bases for diagnostic tasks (i.e., list of symptoms produced by each fault, in linguistic terms described by fuzzy sets) as constrained optimisation problems. The proposed setting allows more flexibility than some fuzzy-logic inference rulebases in the specification of the diagnostic rules in a transparent, user-understandable way (in a first approximation, rules map to zeros and ones in a matrix), using widely-known techniques such as linear and quadratic programming.

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Paper Citation


in Harvard Style

Sala A., Esparza A., Ariño C. and V. Roig J. (2006). ENCODING FUZZY DIAGNOSIS RULES AS OPTIMISATION PROBLEMS . In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-972-8865-59-7, pages 34-39. DOI: 10.5220/0001203100340039


in Bibtex Style

@conference{icinco06,
author={Antonio Sala and Alicia Esparza and Carlos Ariño and Jose V. Roig},
title={ENCODING FUZZY DIAGNOSIS RULES AS OPTIMISATION PROBLEMS},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2006},
pages={34-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001203100340039},
isbn={978-972-8865-59-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - ENCODING FUZZY DIAGNOSIS RULES AS OPTIMISATION PROBLEMS
SN - 978-972-8865-59-7
AU - Sala A.
AU - Esparza A.
AU - Ariño C.
AU - V. Roig J.
PY - 2006
SP - 34
EP - 39
DO - 10.5220/0001203100340039