Dry Bulk Shipping Fuzzy Time Series Prediction

The dry bulk shipping market is the important part of the whole shipping market. The market's construction is shaped to meet the need of the marine traffic of the international trade. In the market, the trade infermation is well-informed, and there are so many ship-owners, and the freight source terminals are highly concentrated, related to the shipping line. The four macroscopical elements which are politics, economy, nature&geography and technology make a heavy influence to the marine traffic and the consructure of the ocean shipping of the dry bulk shipping market.The marine traffic caused by the dry bulk international trade is dynamically changed. Except the historical statistics, it is an impossible task to have an accurate picture of the future marine traffic. There is not a clear function coincidence relation between the marine traffic and the time, such as y=x. It is certain that the international trade of the dry bulk complete the contract through delivering the cargo on time by the ocean shipping. But it is not certain to when and how much the marine traffic take place. The dissertaion consider such uncertainty as a kind of fuzziness.It should adopt the methods of fuzzy forecasting to forecast the future which have the whole or part of fuzzy characteratics. The methods of fuzzy forecasting differ from the methods of classic forecasting lies in the different sets. The classic methods are cantor set, while the fuzzy is fuzzy set.The time series forecasting are acceptable for those fields which just want to forecast the target's future development trend and care little or hard to care the other influence elements, while the target's historical stastics is neraly intergrity at least. The fuzzy time series forecasting differ from classic time series forecasting is lead in the conception, named membership function which contribute much to figure the method.As a result, the dissertation use the predecessor's research findings for reference and lead the fuzzy time series forecasting model in forecasting the recent marine traffic of dry bulk, and adopt the methods to separately build the foodstuff, iron ore and coal recent marine traffic forecasting models whose applicability are proved by the theory and figuring the illustration. Hereinto, the foodstuff is fuzzy smoothness model, which use the fuzzy moving-average method and the data color moving-average method separately to build the model, which better than classic moving-average method showed by the calculated sample; while the iron ore and coal is fuzzy polynomial forecast model, which are interval prediction models, which are interval prediction model whose calculated sample are satisfied.