基于组合预测模型的世界海运周转量预测分析

世界海运周转量是衡量未来航运市场运力需求的直接体现,在确定航运市场和船舶市场的发展趋势方面具有关键作用。针对世界海运周转量受到众多复杂因素影响的现实,基于传统的单个预测方法,分别采用时间序列、灰色系统、神经网络方法对世界海运周转量进行预测,然后再对单个预测方法进行加权组合,建立组合预测模型进行海运周转量的预测,预测结果表明:组合预测模型能够得到更加可靠的结果。

Forecasts of Seaborne Trade Turnover Volume Based on Combination Forecast Methods

Development and change in world seaborne trade turnover volume has extremely important influence on shipping market and ship market.It also plays key role in the analysis of development trend of these two markets.However,the change of world seaborne trade turnover volume is affected by a series of extremely complex factors and forecast of its change is greatly difficult with common methods.Based on individual and traditional forecasting method,time series,gray system method and neural network algorithm are applied to predict the world seaborne trade turnover volume respectively,and then the three methods are combined and applied to the prediction.The result shows that combination method could achieve more accurate forecast effect.