摘要
针对传统GM预测模型的局限性,介绍了改进的GM-Markov综合预测模型的原理,应用范围及优缺点。运用GM-Markov综合预测模型对上海市汽车货运量进行了预测分析,结果表明:灰色—马尔可夫预测模型即能预测汽车货运量参数随机时间序列数据的总体趋势,又能适应波动性较大的随机序列变化,灰色—马尔可夫预测模型预测精度高于GM(1,1)模型的预测精度。该方法可以作为汽车货运量预测的理想工具。最后,就GM-Markov综合预测模型需进一步研究的问题进行了讨论,给出建议。
Aiming to limitation of traditional GM model,an improved GM model based on Markov theory,application scope,strengths and weakness are presented.Through the application of GM-Markov model in forecasting of highway freight traffic volume in Shanghai,it shows： that the model can well and truly forecast the evolvement and changing tread of the data series status.The precision of gray-Markov model for forecast is better than that of gray model.which may be an ideal tool for highway freight traffic volume forecasting.Finally,the problem for future researching of the GM-Markov forecasting model is discussed and relative suggestions are provided.
出处
《机械设计与制造》
北大核心
2011年第8期63-65,共3页
Machinery Design & Manufacture
基金
上海高校知识创新工程(085工程)建设项目资助(JZ0901)
