Evaluation criteria on down-compatibility degree of fuzzy inference mechanism

Chao Deng; Mao Zu Guo; Ya Dong Wang

Evaluation criteria on down-compatibility degree of fuzzy inference mechanism

Chao Deng^*
, Mao Zu Guo
, Ya Dong Wang

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

Being not down-compatible with classical two-value logic inference mechanism, fuzzy inference mechanism (FIM) would get absurd conclusions even in the simplest cases. To strictly evaluate down-compatibility degree and to build new FIM with high down-compatibility degree, a series of formulized criterions are presented based on compatibility of truth space and match modes, and logic consistence of conclusions derived by homologous composite premises from different FIMs. These criteria could offer both formal evaluation scales and revise guidelines. According to these criteria, some FIMs are lower in terms of down-compatibility degree and then revised up to the highest degree under its guidelines.

Original language	English
Title of host publication	2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Pages	2418-2423
Number of pages	6
State	Published - 2005
Externally published	Yes
Event	International Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China Duration: 18 Aug 2005 → 21 Aug 2005

Publication series

Name	2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

Conference

Conference	International Conference on Machine Learning and Cybernetics, ICMLC 2005
Country/Territory	China
City	Guangzhou
Period	18/08/05 → 21/08/05

Keywords

Down-compatibility
Fuzzy inference mechanism
Truth assignment
Two-value logic inference mechanism

Cite this

@inproceedings{b63dc11adf83447d8dd6c42e46637fbf,

title = "Evaluation criteria on down-compatibility degree of fuzzy inference mechanism",

abstract = "Being not down-compatible with classical two-value logic inference mechanism, fuzzy inference mechanism (FIM) would get absurd conclusions even in the simplest cases. To strictly evaluate down-compatibility degree and to build new FIM with high down-compatibility degree, a series of formulized criterions are presented based on compatibility of truth space and match modes, and logic consistence of conclusions derived by homologous composite premises from different FIMs. These criteria could offer both formal evaluation scales and revise guidelines. According to these criteria, some FIMs are lower in terms of down-compatibility degree and then revised up to the highest degree under its guidelines.",

keywords = "Down-compatibility, Fuzzy inference mechanism, Truth assignment, Two-value logic inference mechanism",

author = "Chao Deng and Guo, \{Mao Zu\} and Wang, \{Ya Dong\}",

year = "2005",

language = "英语",

isbn = "078039092X",

series = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",

pages = "2418--2423",

booktitle = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",

note = "International Conference on Machine Learning and Cybernetics, ICMLC 2005 ; Conference date: 18-08-2005 Through 21-08-2005",

}

Deng, C, Guo, MZ & Wang, YD 2005, Evaluation criteria on down-compatibility degree of fuzzy inference mechanism. in 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005. 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005, pp. 2418-2423, International Conference on Machine Learning and Cybernetics, ICMLC 2005, Guangzhou, China, 18/08/05.

Evaluation criteria on down-compatibility degree of fuzzy inference mechanism. / Deng, Chao; Guo, Mao Zu; Wang, Ya Dong.
2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005. 2005. p. 2418-2423 (2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005).

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

TY - GEN

T1 - Evaluation criteria on down-compatibility degree of fuzzy inference mechanism

AU - Deng, Chao

AU - Guo, Mao Zu

AU - Wang, Ya Dong

PY - 2005

Y1 - 2005

N2 - Being not down-compatible with classical two-value logic inference mechanism, fuzzy inference mechanism (FIM) would get absurd conclusions even in the simplest cases. To strictly evaluate down-compatibility degree and to build new FIM with high down-compatibility degree, a series of formulized criterions are presented based on compatibility of truth space and match modes, and logic consistence of conclusions derived by homologous composite premises from different FIMs. These criteria could offer both formal evaluation scales and revise guidelines. According to these criteria, some FIMs are lower in terms of down-compatibility degree and then revised up to the highest degree under its guidelines.

AB - Being not down-compatible with classical two-value logic inference mechanism, fuzzy inference mechanism (FIM) would get absurd conclusions even in the simplest cases. To strictly evaluate down-compatibility degree and to build new FIM with high down-compatibility degree, a series of formulized criterions are presented based on compatibility of truth space and match modes, and logic consistence of conclusions derived by homologous composite premises from different FIMs. These criteria could offer both formal evaluation scales and revise guidelines. According to these criteria, some FIMs are lower in terms of down-compatibility degree and then revised up to the highest degree under its guidelines.

KW - Down-compatibility

KW - Fuzzy inference mechanism

KW - Truth assignment

KW - Two-value logic inference mechanism

UR - https://www.scopus.com/pages/publications/28444479877

M3 - 会议稿件

AN - SCOPUS:28444479877

SN - 078039092X

SN - 9780780390928

T3 - 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

SP - 2418

EP - 2423

BT - 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

T2 - International Conference on Machine Learning and Cybernetics, ICMLC 2005

Y2 - 18 August 2005 through 21 August 2005

ER -

Evaluation criteria on down-compatibility degree of fuzzy inference mechanism

Abstract

Publication series

Conference

Keywords

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Cite this