Tolerance relation based granular space

Zheng Zheng; Hong Hu; Zhongzhi Shi

Tolerance relation based granular space

Zheng Zheng^*
, Hong Hu
, Zhongzhi Shi

^*Corresponding author for this work

CAS - Institute of Computing Technology
University of Chinese Academy of Sciences

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

Abstract

Granular computing as an enabling technology and as such it cuts across a broad spectrum of disciplines and becomes important to many areas of applications. In this paper, the notions of tolerance relation based information granular space are introduced and formalized mathematically. It is a uniform model to study problems in model recognition and machine learning. The key strength of the model is the capability of granulating knowledge in both consecutive and discrete attribute space based on tolerance relation. Such capability is reestablished in granulation and an application in information classification is illustrated. Simulation results show the model is effective and efficient.

Original language	English
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Pages	682-691
Number of pages	10
State	Published - 2006
Externally published	Yes
Event	High-Power Diode Laser Technology and Applications IV - San Jose, CA, United States Duration: 23 Jan 2006 → 25 Jan 2006

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	6104
ISSN (Print)	0277-786X

Conference

Conference	High-Power Diode Laser Technology and Applications IV
Country/Territory	United States
City	San Jose, CA
Period	23/01/06 → 25/01/06

Cite this

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title = "Tolerance relation based granular space",

abstract = "Granular computing as an enabling technology and as such it cuts across a broad spectrum of disciplines and becomes important to many areas of applications. In this paper, the notions of tolerance relation based information granular space are introduced and formalized mathematically. It is a uniform model to study problems in model recognition and machine learning. The key strength of the model is the capability of granulating knowledge in both consecutive and discrete attribute space based on tolerance relation. Such capability is reestablished in granulation and an application in information classification is illustrated. Simulation results show the model is effective and efficient.",

author = "Zheng Zheng and Hong Hu and Zhongzhi Shi",

year = "2006",

language = "英语",

isbn = "0819461466",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

pages = "682--691",

booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

note = "High-Power Diode Laser Technology and Applications IV ; Conference date: 23-01-2006 Through 25-01-2006",

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T1 - Tolerance relation based granular space

AU - Zheng, Zheng

AU - Hu, Hong

AU - Shi, Zhongzhi

PY - 2006

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N2 - Granular computing as an enabling technology and as such it cuts across a broad spectrum of disciplines and becomes important to many areas of applications. In this paper, the notions of tolerance relation based information granular space are introduced and formalized mathematically. It is a uniform model to study problems in model recognition and machine learning. The key strength of the model is the capability of granulating knowledge in both consecutive and discrete attribute space based on tolerance relation. Such capability is reestablished in granulation and an application in information classification is illustrated. Simulation results show the model is effective and efficient.

AB - Granular computing as an enabling technology and as such it cuts across a broad spectrum of disciplines and becomes important to many areas of applications. In this paper, the notions of tolerance relation based information granular space are introduced and formalized mathematically. It is a uniform model to study problems in model recognition and machine learning. The key strength of the model is the capability of granulating knowledge in both consecutive and discrete attribute space based on tolerance relation. Such capability is reestablished in granulation and an application in information classification is illustrated. Simulation results show the model is effective and efficient.

UR - https://www.scopus.com/pages/publications/33645981640

M3 - 会议稿件

AN - SCOPUS:33645981640

SN - 0819461466

SN - 9780819461469

T3 - Proceedings of SPIE - The International Society for Optical Engineering

SP - 682

EP - 691

BT - Proceedings of SPIE - The International Society for Optical Engineering

T2 - High-Power Diode Laser Technology and Applications IV

Y2 - 23 January 2006 through 25 January 2006

ER -

Tolerance relation based granular space

Abstract

Publication series

Conference

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