The purpose of this thesis is to developing and exploiting an intelligent system for collision prevention, namely “Intelligent Collision Prevention Expert System for Navigation”(NICPES). The NICPES has a multi-unit and layering Knowledge Base systematic structure and a multi-unit Knowledge Representation (KR) which based on frame KR, production rule KR, procedure KR and neural network KR, to represent and store all kinds of knowledge for navigation collision prevention. The NICPES also builds a multi-inference system, which based on analogy inference, forward illation inference, conversion inference, neural network inference and meta-rule inference, to overcome the shortcoming of unitary inference. For-some problems in collision prevention region, the NICPES builds a set of models to solve them. These models comprise the models of judging collision risk, the model of determining collision prevention time and the model of classifying encounter situation. For multi-ship encounter situation, the NICPES puts forward a tactics to choose optimal collision prevention scheme based on Analytic Hierarchy Process (AHP) and builds a mathematical model that will be used to determine the optimal angle and sailing time during ship's turning for multi and single ship encounter situation. The simulation experiments show that the NICPES can analyze and judge various sailing cases and encounter situation ,and offer a reasonable scheme, which settle the collision problem effectively and ensure the sailing safety.