DocumentCode :
711967
Title :
Situation Assessment Approach Based on a Hierarchic Multi-timescale Bayesian Network
Author :
Chen Li ; Mingyuan Cao ; Lihua Tian
Author_Institution :
Sch. of Software Eng., Xi´an Jiaotong Univ., Xi´an, China
fYear :
2015
fDate :
24-26 April 2015
Firstpage :
911
Lastpage :
915
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 :
belief networks; ubiquitous computing; adaptive situation assessment; district network structures; hierarchic Bayesian networks; hierarchic multitimescale Bayesian network; modular Bayesian network; situation assessment approach; update parameters; Adaptation models; Atmospheric modeling; Bayes methods; Cognition; Information processing; Sensors; Stochastic processes; DBN; Situation assessment; hierarchic Baysian Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-6849-0
Type :
conf
DOI :
10.1109/ICISCE.2015.207
Filename :
7120747
Link To Document :
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