Discrete fuzzy systems: The aggregation operator

Antonio Hernández Zavala; Jorge Adalberto Huerta Ruelas; Arodi Rafael Carballo Domínguez; Oscar Camacho Nieto

doi:10.1109/FUZZ-IEEE.2013.6622380

Discrete fuzzy systems: The aggregation operator

Antonio Hernández Zavala, Jorge Adalberto Huerta Ruelas, Arodi Rafael Carballo Domínguez, Oscar Camacho Nieto

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Knowledge-based systems have the ability to realize inferences out of pre-defined rules. As the antecedents are driven into the fuzzy system, the system infers to obtain the consequents. These consequents are used to obtain crisp output data. The aggregation operator combines these consequents to obtain a unified shape from which a unique result can be obtained. The way to handle the aggregation varies according to the type of membership functions involved. This paper presents a way of realizing aggregation operation when the membership functions are represented by means of a-levels, showing that this case is suitable for discrete fuzzy system implementations.

Original language	English
Title of host publication	FUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2013.6622380
State	Published - 2013
Event	2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 - Hyderabad, India Duration: 7 Jul 2013 → 10 Jul 2013

Publication series

Name	IEEE International Conference on Fuzzy Systems
ISSN (Print)	1098-7584

Conference

Conference	2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013
Country/Territory	India
City	Hyderabad
Period	7/07/13 → 10/07/13

Keywords

Aggregation
Discrete numbers
Fuzzy systems
Inference systems

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10.1109/FUZZ-IEEE.2013.6622380

Cite this

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title = "Discrete fuzzy systems: The aggregation operator",

abstract = "Knowledge-based systems have the ability to realize inferences out of pre-defined rules. As the antecedents are driven into the fuzzy system, the system infers to obtain the consequents. These consequents are used to obtain crisp output data. The aggregation operator combines these consequents to obtain a unified shape from which a unique result can be obtained. The way to handle the aggregation varies according to the type of membership functions involved. This paper presents a way of realizing aggregation operation when the membership functions are represented by means of a-levels, showing that this case is suitable for discrete fuzzy system implementations.",

keywords = "Aggregation, Discrete numbers, Fuzzy systems, Inference systems",

author = "Zavala, {Antonio Hern{\'a}ndez} and Ruelas, {Jorge Adalberto Huerta} and Dom{\'i}nguez, {Arodi Rafael Carballo} and Nieto, {Oscar Camacho}",

year = "2013",

doi = "10.1109/FUZZ-IEEE.2013.6622380",

language = "Ingl{\'e}s",

isbn = "9781479900220",

series = "IEEE International Conference on Fuzzy Systems",

booktitle = "FUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems",

note = "2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 ; Conference date: 07-07-2013 Through 10-07-2013",

}

Zavala, AH , Ruelas, JAH, Domínguez, ARC & Nieto, OC 2013, Discrete fuzzy systems: The aggregation operator. in FUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems., 6622380, IEEE International Conference on Fuzzy Systems, 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013, Hyderabad, India, 7/07/13. https://doi.org/10.1109/FUZZ-IEEE.2013.6622380

Discrete fuzzy systems: The aggregation operator. / Zavala, Antonio Hernández ; Ruelas, Jorge Adalberto Huerta; Domínguez, Arodi Rafael Carballo et al.
FUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems. 2013. 6622380 (IEEE International Conference on Fuzzy Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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T2 - 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013

AU - Zavala, Antonio Hernández

AU - Ruelas, Jorge Adalberto Huerta

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AU - Nieto, Oscar Camacho

PY - 2013

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AB - Knowledge-based systems have the ability to realize inferences out of pre-defined rules. As the antecedents are driven into the fuzzy system, the system infers to obtain the consequents. These consequents are used to obtain crisp output data. The aggregation operator combines these consequents to obtain a unified shape from which a unique result can be obtained. The way to handle the aggregation varies according to the type of membership functions involved. This paper presents a way of realizing aggregation operation when the membership functions are represented by means of a-levels, showing that this case is suitable for discrete fuzzy system implementations.

KW - Aggregation

KW - Discrete numbers

KW - Fuzzy systems

KW - Inference systems

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M3 - Contribución a la conferencia

AN - SCOPUS:84887850601

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T3 - IEEE International Conference on Fuzzy Systems

BT - FUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems

Y2 - 7 July 2013 through 10 July 2013

ER -

Discrete fuzzy systems: The aggregation operator

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