Prediction of Traffic Volume in Bridge Load Random Process Based on Grey Markov Chain

Abstract

In order to overcome the deficiencies of the grey prediction method, based on grey model prediction, an improved grey Markov chain model for prediction of the traffic volume in bridge random load process was proposed. The grey prediction curve of the model reflects the historical development trend of the traffic volume, and Markov prediction reflects the impact of random fluctuation on traffic volume. So this method takes into account the trend and fluctuation factors to predict the outcome, it can overcome the limitation of the traffic volume prediction by a single prediction model. Combined with the actual situation, the traffic volume can be predicted accurately and comprehensively. Based on the existing traffic volume statistics, the accuracy of the model was tested, and the traffic volume of 2007 was predicted by the model. Examples of calculation and analysis show that the model is of high precision and the predicted outcome meets the actual status basically. It is effective to predict traffic volume by the grey Markov theory.