Improved Dynamic Bayesian Networks in Sea-Battlefield Situation Assessment

Yong Tao Yu; Ying Ding

doi:10.4028/www.scientific.net/AMR.875-877.2190

Paper Titles

Research on Familiar Fault Diagnosis Technology to Electrical System of Auto Crane
p.2170

Study on Mechanical Engineering Measurement and Control Experimental Technique
p.2174

An Intelligent Transport System Methodology to Identify and Controlling of Faulty Vehicles
p.2179

Jamming Effectiveness of Noise Amplitude Modulation Signal to Pesudo-Random Code Fuze
p.2184

Improved Dynamic Bayesian Networks in Sea-Battlefield Situation Assessment
p.2190

Study on Hardware-in-the-Loop Simulation System for Navigation and Control of UUV
p.2196

The Modular Parallel Mechanism of Single-Driven Multi-Legged Robots
p.2201

Application of Electronic Nose for Detection of Wine-Aging Methods
p.2206

Oscillation for a Mechanical Controlled System with Time Delay
p.2214

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 875-877Improved Dynamic Bayesian Networks in...

Improved Dynamic Bayesian Networks in Sea-Battlefield Situation Assessment

Abstract:

How to efficiently evaluate the dynamic and complex the sea-battlefield situation facing the reality of the problem is the operational decision support. According to research sea-battlefield situation assessment based on improved dynamic Bayesian networks. First constructed the sea-battlefield situation assessment Bayesian networks model; second specific assessment task to establish the corresponding dynamic Bayesian networks; again reintroduced extended hidden variables, supplemental situation information to construct improved dynamic Bayesian networks; finally, according to the battlefield event reasoning, complete sea-battlefield situation assessment.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 875-877)

Pages:

2190-2195

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.875-877.2190

Citation:

Cite this paper

Online since:

February 2014

Authors:

Yong Tao Yu, Ying Ding

Keywords:

Dynamic Bayesian, Sea-Battlefield, Situation Assessment

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Lei Yingjie. Based on the intuitive fuzzy decision battlefield situation assessment method [J]. Electronic Journal 2006, 34 (12): 2175-2179.

Google Scholar

[2] Zhang Hongwei. DBNS learning and the approximate reasoning model study [A]. The fourth automatic control theory International Conference, Shanghai, (2002).

Google Scholar

[3] Santos E J r．a unified framework for reasoning with time and uncertainty[J]. International Journal of Approximate Reasoning, 1999, 20(3): 191-216.

Google Scholar

[4] Mahoney S M. Constructing Situation Specific Belief Networks[EB/OL]. [2008-6-30].

Google Scholar

[5] Hall D L．Handbook of multi-sensor data fusion[M], Washington DC: CRC Press, 2001.

Google Scholar

[6] Tian F. Learning Bayesian networks with hidden variables using the combination of EM algorithm[A]. Pacific-Asia Conference on Data Mining, Hongkong, 2001.

Google Scholar

[7] KILIC R . A practical guide for studying Chua's circuits [M]. [S. l. ]: World Scientific，2010.

Google Scholar