An intelligent decision support system to ship anti-collision in multi-ship encounter

A novel anti-collision fuzzy model is proposed to decide whether anti-collision action should be taken. To build a supporting system to ship anti-collision in multiple ships encounter, a last time to take action (LTTA) concept is proposed without considering any psychological factors. To obtain a LTTA capability in the anti-collision model, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A kind of neural network architecture is used to train the parameters of the fuzzy inference system (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. The hybrid algorithm applies a combination of the least-squares method and back-propagation gradient descent method. This network can be considered to be a self-learning system.