Situation assessment approach based on a hierarchic multi-timescale bayesian network

Chen Li; Mingyuan Cao; Lihua Tian

doi:10.1109/ICISCE.2015.207

Situation assessment approach based on a hierarchic multi-timescale bayesian network

Chen Li
, Mingyuan Cao
, Lihua Tian

Faculty of Electronic and Information Engineering

Xi'an Jiaotong University

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

6 Scopus citations

Abstract

In this paper, situation assessment in the battle field is described by the modular Bayesian network, and a method is proposed for adaptive situation assessment using a hierarchic Bayesian Networks. For different levels, district network structures are adopted to infer situation and adaptively update parameters of network with different timescale. Specially, dynamic Bayesian networks are utilized in the lower level networks, taking full advantage of the direct measurement of sensors and improving the robustness of the assessment system. A simulation is provided to indicate how to structure the network model, infer situation and update parameters for hierarchic Bayesian networks. The simulation results illustrate the validity of the proposed method.

Original language	English
Title of host publication	Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015
Editors	Shaozi Li, Ying Dai, Yun Cheng
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	911-915
Number of pages	5
ISBN (Electronic)	9781467368506
DOIs	https://doi.org/10.1109/ICISCE.2015.207
State	Published - 9 Jun 2015
Event	2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015 - Shanghai, China Duration: 24 Apr 2015 → 26 Apr 2015

Publication series

Name	Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015

Conference

Conference	2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015
Country/Territory	China
City	Shanghai
Period	24/04/15 → 26/04/15

Keywords

DBN
Hierarchic Baysian Network
Situation assessment

Access to Document

10.1109/ICISCE.2015.207

Cite this

Li, C., Cao, M., & Tian, L. (2015). Situation assessment approach based on a hierarchic multi-timescale bayesian network. In S. Li, Y. Dai, & Y. Cheng (Eds.), Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015 (pp. 911-915). Article 7120747 (Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICISCE.2015.207

Li, Chen ; Cao, Mingyuan ; Tian, Lihua. / Situation assessment approach based on a hierarchic multi-timescale bayesian network. Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015. editor / Shaozi Li ; Ying Dai ; Yun Cheng. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 911-915 (Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015).

@inproceedings{f4d4ae9238854bd5ba022c349856530c,

title = "Situation assessment approach based on a hierarchic multi-timescale bayesian network",

abstract = "In this paper, situation assessment in the battle field is described by the modular Bayesian network, and a method is proposed for adaptive situation assessment using a hierarchic Bayesian Networks. For different levels, district network structures are adopted to infer situation and adaptively update parameters of network with different timescale. Specially, dynamic Bayesian networks are utilized in the lower level networks, taking full advantage of the direct measurement of sensors and improving the robustness of the assessment system. A simulation is provided to indicate how to structure the network model, infer situation and update parameters for hierarchic Bayesian networks. The simulation results illustrate the validity of the proposed method.",

keywords = "DBN, Hierarchic Baysian Network, Situation assessment",

author = "Chen Li and Mingyuan Cao and Lihua Tian",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015 ; Conference date: 24-04-2015 Through 26-04-2015",

year = "2015",

month = jun,

day = "9",

doi = "10.1109/ICISCE.2015.207",

language = "英语",

series = "Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "911--915",

editor = "Shaozi Li and Ying Dai and Yun Cheng",

booktitle = "Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015",

}

Li, C, Cao, M & Tian, L 2015, Situation assessment approach based on a hierarchic multi-timescale bayesian network. in S Li, Y Dai & Y Cheng (eds), Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015., 7120747, Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015, Institute of Electrical and Electronics Engineers Inc., pp. 911-915, 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015, Shanghai, China, 24/04/15. https://doi.org/10.1109/ICISCE.2015.207

Situation assessment approach based on a hierarchic multi-timescale bayesian network. / Li, Chen; Cao, Mingyuan; Tian, Lihua.
Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015. ed. / Shaozi Li; Ying Dai; Yun Cheng. Institute of Electrical and Electronics Engineers Inc., 2015. p. 911-915 7120747 (Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015).

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

TY - GEN

T1 - Situation assessment approach based on a hierarchic multi-timescale bayesian network

AU - Li, Chen

AU - Cao, Mingyuan

AU - Tian, Lihua

PY - 2015/6/9

Y1 - 2015/6/9

N2 - In this paper, situation assessment in the battle field is described by the modular Bayesian network, and a method is proposed for adaptive situation assessment using a hierarchic Bayesian Networks. For different levels, district network structures are adopted to infer situation and adaptively update parameters of network with different timescale. Specially, dynamic Bayesian networks are utilized in the lower level networks, taking full advantage of the direct measurement of sensors and improving the robustness of the assessment system. A simulation is provided to indicate how to structure the network model, infer situation and update parameters for hierarchic Bayesian networks. The simulation results illustrate the validity of the proposed method.

AB - In this paper, situation assessment in the battle field is described by the modular Bayesian network, and a method is proposed for adaptive situation assessment using a hierarchic Bayesian Networks. For different levels, district network structures are adopted to infer situation and adaptively update parameters of network with different timescale. Specially, dynamic Bayesian networks are utilized in the lower level networks, taking full advantage of the direct measurement of sensors and improving the robustness of the assessment system. A simulation is provided to indicate how to structure the network model, infer situation and update parameters for hierarchic Bayesian networks. The simulation results illustrate the validity of the proposed method.

KW - DBN

KW - Hierarchic Baysian Network

KW - Situation assessment

UR - https://www.scopus.com/pages/publications/84938783548

U2 - 10.1109/ICISCE.2015.207

DO - 10.1109/ICISCE.2015.207

M3 - 会议稿件

AN - SCOPUS:84938783548

T3 - Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015

SP - 911

EP - 915

BT - Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015

A2 - Li, Shaozi

A2 - Dai, Ying

A2 - Cheng, Yun

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015

Y2 - 24 April 2015 through 26 April 2015

ER -

Li C, Cao M, Tian L. Situation assessment approach based on a hierarchic multi-timescale bayesian network. In Li S, Dai Y, Cheng Y, editors, Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 911-915. 7120747. (Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015). doi: 10.1109/ICISCE.2015.207

Situation assessment approach based on a hierarchic multi-timescale bayesian network

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