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Indexed by:会议论文

Date of Publication:2008-01-01

Included Journals:CPCI-S

Page Number:325-328

Key Words:traffic forecasting; combining forecasting; gray theory; regression forecasting

Abstract:Traffic forecasting is an important problem of traffic planning and transportation management. Gray and regression model are widely used to forecasting traffic with different applicable conditions and effects. Generally, the Gray Model (GM) considers historical traffic, but hardly relative factors such as economics and population. And the complex relationship between traffic and its relative factors should be supposed before regression forecasting. Therefore in the paper, their combining forecasting models with weighted arithmetic average, weighted average square sum and weighted ratio average are proposed to avoid their individual limitation and to improve traffic forecast. Experiments show that the combining model is capable to improve the precision of prediction by selecting suitable combining styles and their coefficients.