Multiple Model Estimation represented by Bayesian Networks

Yan Liang; Donghua Zhou; Quan Pan

Multiple Model Estimation represented by Bayesian Networks

Yan Liang, Donghua Zhou, Quan Pan

School of Automation

Tsinghua University

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

Multiple Model Estimation (MME) in hybrid systems, as a powerful approach to adaptive estimation, has been widely applied in a great deal of attention due to its unique power to handle problems with both structural and parametric uncertainties. In this paper, multiple well-known methods in MME are represented in the form of Bayesian Networks (BN), which is widely used in Artificial Intelligence. The following discusses imply that MME may be a special case of BN.

Original language	English
Pages	863-866
Number of pages	4
State	Published - 2002
Event	Proceedings of the 4th World Congress on Intelligent Control and Automation - Shanghai, China Duration: 10 Jun 2002 → 14 Jun 2002

Conference

Conference	Proceedings of the 4th World Congress on Intelligent Control and Automation
Country/Territory	China
City	Shanghai
Period	10/06/02 → 14/06/02

Cite this

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title = "Multiple Model Estimation represented by Bayesian Networks",

abstract = "Multiple Model Estimation (MME) in hybrid systems, as a powerful approach to adaptive estimation, has been widely applied in a great deal of attention due to its unique power to handle problems with both structural and parametric uncertainties. In this paper, multiple well-known methods in MME are represented in the form of Bayesian Networks (BN), which is widely used in Artificial Intelligence. The following discusses imply that MME may be a special case of BN.",

author = "Yan Liang and Donghua Zhou and Quan Pan",

year = "2002",

language = "英语",

pages = "863--866",

note = "Proceedings of the 4th World Congress on Intelligent Control and Automation ; Conference date: 10-06-2002 Through 14-06-2002",

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TY - CONF

T1 - Multiple Model Estimation represented by Bayesian Networks

AU - Liang, Yan

AU - Zhou, Donghua

AU - Pan, Quan

PY - 2002

Y1 - 2002

N2 - Multiple Model Estimation (MME) in hybrid systems, as a powerful approach to adaptive estimation, has been widely applied in a great deal of attention due to its unique power to handle problems with both structural and parametric uncertainties. In this paper, multiple well-known methods in MME are represented in the form of Bayesian Networks (BN), which is widely used in Artificial Intelligence. The following discusses imply that MME may be a special case of BN.

AB - Multiple Model Estimation (MME) in hybrid systems, as a powerful approach to adaptive estimation, has been widely applied in a great deal of attention due to its unique power to handle problems with both structural and parametric uncertainties. In this paper, multiple well-known methods in MME are represented in the form of Bayesian Networks (BN), which is widely used in Artificial Intelligence. The following discusses imply that MME may be a special case of BN.

UR - http://www.scopus.com/inward/record.url?scp=0036945993&partnerID=8YFLogxK

M3 - 论文

AN - SCOPUS:0036945993

SP - 863

EP - 866

T2 - Proceedings of the 4th World Congress on Intelligent Control and Automation

Y2 - 10 June 2002 through 14 June 2002

ER -

Multiple Model Estimation represented by Bayesian Networks

Abstract

Conference

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