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

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外文摘要：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。

外文关键词：

Bayes methodsknowledge representationmilitary computingpattern matchingAI systemartificial intelligence systemdynamic Bayesian networkdynamic systemknowledge representationknowledge skillsmultidimensional systemnonlinear systempattern matchingprobabilityreasoning abilityrule setsea-battlefield situation assessmenttime factorAircraftBayes methodsCognitionMeteorologyPattern matchingReal-time systemsTime factorsBayesian NetworkPattern MatchingSea-battlefieldSituation assessment

作者：

Jun Ma、Li Liu

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作者单位：

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

会议名称：

IEEE Chinese Guidance, Navigation and Control Conference

会议地点：

Yantai(CN)

会议母体文献：

2014 IEEE Chinese Guidance, Navigation and Control Conference

页码：

1764-1769

出版时间：

2014

DOI：

10.1109/CGNCC.2014.7007450