Combined Prediction of Transport Capacity in Henan Province

In the paper, the linear regression reflects the tendency of straight line but inevitably there exists big error between actual and fitted values among some points. In this paper, firstly, the raw data sequence is classified into two parts namely aberrant and normal data. Secondly, using the principle of non-equidistant GM (1, 1), the authors derive the aberrant forecast function. In addition, for other normal data points left, one new linear regression function is established. According to two groups of the actual and estimated values, the authors derive the two coefficients of the combined models. Finally, the article selects the cargo turnover quantity as the variable representing the transport capacity level of Henan by using the grey relational analysis between freight traffic volume, cargo turnover quantity and gross domestic product (GDP) respectively based on the data of Henan Province from 1999 to 2008. The paper establishes the combined method by using the actual and forecasting values of 2007 and 2008. Using the data, the authors can make predictions for the next three years' demand quantities of Henan logistics industry. Finally, the results demonstrate the combined result is proved to be precise and reliable.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 4004-4010
  • Monograph Title: ICLEM 2010: Logistics For Sustained Economic Development: Infrastructure, Information, Integration

Subject/Index Terms

Filing Info

  • Accession Number: 01525529
  • Record Type: Publication
  • ISBN: 9780784411391
  • Files: TRIS, ASCE
  • Created Date: Nov 12 2013 1:54PM