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.


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    Title :

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


    Contributors:
    Ma, Jun (author) / Liu, Li (author)


    Publication date :

    2014-08-01


    Size :

    207678 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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