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Authors: Antonio Sala ; Alicia Esparza ; Carlos Ariño and Jose V. Roig

Affiliation: Univ. Politécnica de Valencia, Spain

Keyword(s): Fault detection and diagnosis, fuzzy mathematical programming, approximate reasoning, optimisation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Expert Systems ; Health Information Systems ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Intelligent Fault Detection and Identification ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Symbolic Systems

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 several formats:
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 3: ICINCO; ISBN 978-972-8865-59-7; ISSN 2184-2809, SciTePress, pages 34-39. DOI: 10.5220/0001203100340039

@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 3: ICINCO},
year={2006},
pages={34-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001203100340039},
isbn={978-972-8865-59-7},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO
TI - ENCODING FUZZY DIAGNOSIS RULES AS OPTIMISATION PROBLEMS
SN - 978-972-8865-59-7
IS - 2184-2809
AU - Sala, A.
AU - Esparza, A.
AU - Ariño, C.
AU - V. Roig, J.
PY - 2006
SP - 34
EP - 39
DO - 10.5220/0001203100340039
PB - SciTePress