SHIP INTELLIGENT ANTI-COLLISION USING SELF-LEARNING NEUROFUZZY

摘要

A novel anti-collision procedure (involving three stages) is addressed in this paper. To obtain a precise Last Minute Action (LMA) 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 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. This network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge.