Networking

Road Traffic Freight Volume Forecast Using Support Vector Machine Combining Forecasting

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Executive Summary

The grey system forecasting model, neural network forecasting model and support vector machine forecasting model are proposed in this paper. Taking the road goods traffic volume from year of 1996 to 2003 in the whole country as a study case, the forecasting results are got by three methods. From the forecasting results, the authors conclude that the accuracy of the support vector machine forecasting method is higher. Analyzing the characteristic of combining forecasting method, based on grey system forecasting model, neural network forecasting model and support vector machine forecasting model, the linear combining forecasting model, neural network combining forecasting model and support vector machine combining forecasting model are set up.

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