A ship based intelligent anti-collision decision-making support system utilizing trial manoeuvres

To provide a novel intelligent anti-collision decision-making support system it is necessary to facilitate a precise anti-collision information capability. In the reported research an innovative self-learning neurofuzzy network is proposed and applied to learn new information adaptively without forgetting old knowledge. To handle imprecise information a fuzzy set interpretation facility is incorporated into the network design. Additionally 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 is obtained from trial manoeuvres. This support system has been developed to help ship operators make a precise anti-collision decision, whilst simultaneously reducing the burden of bridge data processing.