Study On The Forecast Technology Of Vessel Sailing Risk In VTS

With the development of maritime trade, the traffic on the sea becomes busy day by day, maritime accidents take place frequently. Conventional management mode is not met the need of sharp vessel traffic development. People take attention more and more on how to use the advanced technology to forecast the dangerous of navigation timely and accurately, thereby ensure the sailing safety, reduce the vessel accident, improve the efficiency of traffic on the sea and protect the ocean environment.Now, VTS (Vessel Traffic Services) is not intelligent enough to predicate and identify the traffic danger on the sea. Aiming at the present situation, this thesis proposes that vessel sailing risk can be forecasted by using artificial neural network, sequentially make VTS more intelligent and reduce the intensity and press of VTS operator.According to the characteristic that the traffic system on the sea is dynamic and time-variance and the advantage that neural network has in solving complicated and nonlinear problems, a method of forecasting the ship accidents with BP neural network is proposed. While analyzing exhaustively to the many factors that influence the ships sailing safety, and combining the characteristic of VTS system in data collecting and the processing, design and build up the model to predicate the dangerous of navigation on BP neural network. At last, use neural network tool box in Matlab to simulate the forecast model of navigation dangerous, and verify the forecast precision of the model by history data about ship accident. The result indicates that this method can forecast exactly the navigation dangerous. It is a feasible method that can be applied in VTS.