The Machine Learning Method of PIDVCA

Building a dynamic collision knowledge base of self-learning is one of the core contents of implementing "personified intelligence" in Personifying Intelligent Decision-making for Vessel Collision Avoidance (short for PIDVCA). In the paper, the machine learning method of PIDVCA combined with offline artificial learning and online machine learning is proposed. The static collision avoidance knowledge is acquired through offline artificial learning, and the isomeric knowledge representation integration method with process knowledge as the carrier is established, and the Dynamic collision avoidance knowledge is acquired through online machine learning guided by inference engine. A large number of simulation results show that the dynamic collision avoidance knowledge base constructed by machine learning can achieve the effect of anthropomorphic intelligent collision avoidance. It is verified by examples that the machine learning method of PIDVCA can realize target perception, target cognition and finally obtain an effective collision avoidance decision-making.