Risk prediction of marine traffic based on Fractal interpolation algorithm

Risk prediction is the key element in risk managements. The commonly quantitative prediction methods approaches focus on reasoning by statistics data. This paper held out the Fractal interpolation algorithm to solve the time series data by means of transferring the discrete data to continue data. On the basis of introduction of fractal theory applying the feasibility to marine traffic accidents, it is presented by evaluating iterated function system and its attractor, which uses fractal interpolation algorithm to handle discrete data aggregating with time series, and then models the risk prediction of marine accidents theoretically. Finally, taking statistic data of marine traffic accidents as case studies, it proves that the data reasoning model is more accurate than common computing algorithm special for high fluctuant curve.