Fuzzy Implication and Compatibility Modification

Valerie Cross; Thomas Sudkamp

doi:10.1109/FUZZY.1993.327486

Fuzzy Implication and Compatibility Modification

Valerie Cross, Thomas Sudkamp

Computer Science and Engineering

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

Abstract

The authors examine the separability of several common families of compatibility modification (CM) inference techniques. CM fuzzy inference separates the evaluation of the antecedent of a rule from the generation of the output. The determination of the degree to which the input matches the antecedent is determined by a compatibility measure and an aggregation operator. The order in which these operations occurs changes the set of applicable rules. Separability conditions are introduced to define circumstances in which rule evaluation is independent of the input evaluation strategy. It is shown that compatibility modification inference using fuzzy partial matching and Minkowski dissimilarity satisfies several separability conditions.

Original language	English
Title of host publication	Proceedings 1993 Second IEEE International Conference on Fuzzy Systems
Publisher	Publ by IEEE
Pages	219-224
Number of pages	6
ISBN (Print)	0-7803-0614-7
DOIs	https://doi.org/10.1109/FUZZY.1993.327486
State	Published - 1993
Event	Second IEEE International Conference on Fuzzy Systems - San Francisco, CA, USA Duration: Mar 28 1993 → Apr 1 1993

Conference

Conference	Second IEEE International Conference on Fuzzy Systems
City	San Francisco, CA, USA
Period	3/28/93 → 4/1/93

ASJC Scopus Subject Areas

General Engineering

Keywords

Computer science
Fuzzy logic
Fuzzy reasoning
Fuzzy sets
Fuzzy systems
Hamming distance
Impedance matching
Interpolation
Knowledge based systems
Labeling

Disciplines

Computer Sciences
Engineering
Mathematics

Access to Document

10.1109/FUZZY.1993.327486License: Unspecified

Cite this

@inproceedings{9dcd263afaa742798511c8418118f3e8,

title = "Fuzzy Implication and Compatibility Modification",

abstract = " The authors examine the separability of several common families of compatibility modification (CM) inference techniques. CM fuzzy inference separates the evaluation of the antecedent of a rule from the generation of the output. The determination of the degree to which the input matches the antecedent is determined by a compatibility measure and an aggregation operator. The order in which these operations occurs changes the set of applicable rules. Separability conditions are introduced to define circumstances in which rule evaluation is independent of the input evaluation strategy. It is shown that compatibility modification inference using fuzzy partial matching and Minkowski dissimilarity satisfies several separability conditions.",

keywords = "Computer science, Fuzzy logic, Fuzzy reasoning, Fuzzy sets, Fuzzy systems, Hamming distance, Impedance matching, Interpolation, Knowledge based systems, Labeling",

author = "Valerie Cross and Thomas Sudkamp",

year = "1993",

doi = "10.1109/FUZZY.1993.327486",

language = "English",

isbn = " 0-7803-0614-7 ",

pages = "219--224",

booktitle = "Proceedings 1993 Second IEEE International Conference on Fuzzy Systems",

publisher = "Publ by IEEE",

note = "Second IEEE International Conference on Fuzzy Systems ; Conference date: 28-03-1993 Through 01-04-1993",

}

TY - GEN

T1 - Fuzzy Implication and Compatibility Modification

AU - Cross, Valerie

AU - Sudkamp, Thomas

PY - 1993

Y1 - 1993

N2 - The authors examine the separability of several common families of compatibility modification (CM) inference techniques. CM fuzzy inference separates the evaluation of the antecedent of a rule from the generation of the output. The determination of the degree to which the input matches the antecedent is determined by a compatibility measure and an aggregation operator. The order in which these operations occurs changes the set of applicable rules. Separability conditions are introduced to define circumstances in which rule evaluation is independent of the input evaluation strategy. It is shown that compatibility modification inference using fuzzy partial matching and Minkowski dissimilarity satisfies several separability conditions.

AB - The authors examine the separability of several common families of compatibility modification (CM) inference techniques. CM fuzzy inference separates the evaluation of the antecedent of a rule from the generation of the output. The determination of the degree to which the input matches the antecedent is determined by a compatibility measure and an aggregation operator. The order in which these operations occurs changes the set of applicable rules. Separability conditions are introduced to define circumstances in which rule evaluation is independent of the input evaluation strategy. It is shown that compatibility modification inference using fuzzy partial matching and Minkowski dissimilarity satisfies several separability conditions.

KW - Computer science

KW - Fuzzy logic

KW - Fuzzy reasoning

KW - Fuzzy sets

KW - Fuzzy systems

KW - Hamming distance

KW - Impedance matching

KW - Interpolation

KW - Knowledge based systems

KW - Labeling

UR - http://www.scopus.com/inward/record.url?scp=0027259569&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027259569&partnerID=8YFLogxK

UR - https://corescholar.libraries.wright.edu/cse/446

U2 - 10.1109/FUZZY.1993.327486

DO - 10.1109/FUZZY.1993.327486

M3 - Conference contribution

SN - 0-7803-0614-7

SP - 219

EP - 224

BT - Proceedings 1993 Second IEEE International Conference on Fuzzy Systems

PB - Publ by IEEE

T2 - Second IEEE International Conference on Fuzzy Systems

Y2 - 28 March 1993 through 1 April 1993

ER -

Fuzzy Implication and Compatibility Modification

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

Other files and links

Cite this