Sea-battlefield situation assessment based on a new method combining dynamic Bayesian network with pattern matching
Jun Ma, Li Liu · 2014
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.