Research On Application Methods Of Chaotic Theory To Marine Traffic Accidents

Recently the vessel traffic accident forecasting is quite important to maritime supervision,management and early warning.The vessel traffic accident is a random event influenced by many kinds of factors.For one hand,information of environment and ships operators are indefinite.For the other,people,the ship and environment contain many kinds of processes with mutual coupling influences.So various factors will vary once the time and the space are changed in the ship's travel.Its complex, polytropic,unknown characteristics constitute ships high nonlinearity of vessel traffic accident.Under the mutual function of many factors,the vessel traffic accident displays its evolved characteristics which are extremely complex and difficult to predict exactly.But along with non-linear theory's development,especially development of chaotic theory,it is possible that we can consider each factor's influence separately to forecast the vessel traffic accidents.This paper utilizes the chaos theory to predict vessel traffic accidents.Using the analysis method of other domains for reference and doing research on vessel traffic accidents' prediction from chaotic angle is a kind of new attempt.The summary of concrete content and current results is as follows:Chaotic and phase-space reconstruction theories are expounded at first,and three methods of computing the phase-space reconstruction parameters are proposed.The phase-space reconstruction leads chaotic theory into time series analysis to recover chaotic attracts in high dimension space and to expose the regularity of chaotic system.Secondly,accident chaos theory is proposed.The chaos characteristics in vehicle traffic accidents are analyzed by accident chaos theory and fault tree,and traffic accident chaos dynamics model is established.Then the chaos attractors are predicted by phase space neighbor-equal-distance method to predict traffic accidents,which provides an effective theory to prevent traffic accidents.Thirdly,how to select phase-space reconstruction parameters is the key problem to the forecasting precision and forecasting scales.After further research this paper introduces the chaotic forcasting model based on phase-space reconstruction.It includes the biggest Lyapunov exponent prediction and adding-weight one-rank local prediction.Subsequently the simulation analysis is carried on by using small data quantity of 500 points from Lorenz map.Then in view of insufficiency in forecasting precision and forecasting scales with conventional method,this paper proposes the improved auto-adapted local forecasting model.From analysis result of simulation experiment,we can see the forecasting precision and forecasting scales are further improved.Finally,as is known to us,the vessel traffic accidents data includes great noise and the time series are very short.But the wavelet theory has good characteristics in the control of singular points and elimination noise.So using the auto-adapted chaotic forecasting model based on the wavelet denoising can enhance the forecast precision to a certain extent and satisfy the practical request.