基于灰色马尔可夫链的桥梁荷载随机过程交通量预测

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

为了克服灰色预测方法的不足,在灰色模型预测方法的基础上,提出灰色马尔可夫链桥梁荷载随机过程交通量预测模型,该模型的灰色预测曲线能反映交通量历史发展趋势,马尔可夫预测可反映随机波动性对交通量预测的影响,从兼顾了趋势值和波动性两方面因素对预测结果的作用,能克服单一预测模型在交通量预测中的局限性,并可结合交通量实际情况,能实现准确、综合预测交通量的目的。在现有交通量统计资料的基础上,对该模型进行了精度检验,并预测出了2007年的交通量。实例计算分析表明,模型精度良好,预测结果与实际状态基本相符,利用灰色马尔可夫理论进行交通量预测是一种行之有效的方法。

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 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 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.