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Different methods of traffic forecast based on real data
2004
European Journal of Operational Research
Different methods to forecast traffic are analysed and discussed. An elementary approach is to develop heuristics based on the statistical analysis of historical data. Daily traffic demand data from 350 inductive loops of the inner city of Duisburg over a period of 2 years served as input. The sets of data are organized into four basic classes and a matching process that assigns these sets into their class automatically is proposed. Furthermore, two models for shortterm forecast are examined:
doi:10.1016/j.ejor.2003.08.005
fatcat:orq4afyfwne5jkl74j2ziwwoqa