Sea-battlefield situation assessment based on a new method combining dynamic Bayesian network with pattern matching

Author

Jun Ma ; Li Liu

Author_Institution

Nat. Key Lab. of Sci. & Technol. on Integrated Control Technol., Beihang Univ., Beijing, China

fYear

2014

fDate

8-10 Aug. 2014

Firstpage

1764

Lastpage

1769

Abstract

Sea-battlefield situation is a dynamic, nonlinear and multi-dimensional system where Artificial Intelligence (AI) system has a good role to play. Bayesian Network has a strong knowledge skills and reasoning ability to solve the problem of sea-battlefield situation assessment. After constructing the network, giving the probability, considering the time factor and then combining with Pattern Matching using a rule set, sea-battlefield situation assessment can be achieved. The knowledge representation will be discussed and how to complete reasoning through Bayesian Network and Pattern Matching will be researched. In the end, a simulation will illustrate the combining method has a good performance in sea-battle-field situation assessment.

Keywords

Bayes methods; knowledge representation; military computing; pattern matching; AI system; artificial intelligence system; dynamic Bayesian network; dynamic system; knowledge representation; knowledge skills; multidimensional system; nonlinear system; pattern matching; probability; reasoning ability; rule set; sea-battlefield situation assessment; time factor; Aircraft; Bayes methods; Cognition; Meteorology; Pattern matching; Real-time systems; Time factors; Bayesian Network; Pattern Matching; Sea-battlefield; Situation assessment;

fLanguage

English

Publisher

ieee

Conference_Titel

Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese

Conference_Location

Yantai

Print_ISBN

978-1-4799-4700-3

Type

conf

DOI

10.1109/CGNCC.2014.7007450

Filename

7007450