The Neural-Fuzzy Approach as a Way of Preventing a Maritime Vessel Accident in a Heavy Traffic Zone

Abstract

The paper dwells on the methodology of neural-fuzzy approach to solving the problem of ship collision prevention in a heavy traffic zone. The authors present the technique of using maneuvering board to form the elements of learning sample. The authors prove that it is rational to use a neural-fuzzy system, where generation is carried out by the lattice method without clustering. The authors investigate the effect of optimization on the quality differences. The researchers define optimal membership functions that are used to generate the input linguistic variables of a neural-fuzzy system.