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为保证城市公交客运相关政策及运力配置的科学性,分析了影响城市公交客运量的相关因素,并应用灰色理论对2004~2009年西安市的城市公交客运量进行了分析,构建序列累加生成数列,建立预测模型并进行了模型残差检验。以-15%,-3%,0,3%为划分阈值,将灰色理论模型的相对误差划分为3个状态区间,应用马尔科夫模型对灰色理论模型的预测结果进行修正,并与实际结果进行比较。研究结果表明:应用指数平滑法,西安市2010,2011年的城市公交客运量的预测结果分别为162 278万、169 867万人,预测误差分别为-3.511 2%,-3.074 0%;应用模糊线性回归模型,预测结果分别为163 976万、171 898万人,预测误差分别为-2.500 3%,-1.914 9%;应用灰色理论,预测结果分别为164 314万、172 458万人,预测误差分别为-2.299 0%,-1.595 4%。应用提出的方法,预测结果分别为166 933万、176 349万人,预测误差分别为0.743 2%,0.621 9%。可见,提出的方法精度较高,满足实际需求。
In order to ensure the scientificity of the policies and capacity allocation of urban public transport, the paper analyzes the relevant factors that affect the urban public transport volume, and uses gray theory to analyze the urban public transport in Xi’an from 2004 to 2009, , Establishes the prediction model and carries on the model residual test. The relative error of the gray theoretical model is divided into three state intervals by -15%, -3% and 0,3%. The Markov model is applied to correct the prediction results of the gray theory model and is compared with the actual results Compare. The results show that the forecasting results of Xi’an urban bus passenger volume in 2010 and 2011 are respectively 162.28 million and 169.867 million by using exponential smoothing method, the prediction errors are -3.511 2% and -3.074 0% respectively; The linear regression models show that the predicted results are 1.6376 million and 17.898 million respectively, the prediction errors are -2.500 3% and 1.914 9%, respectively. The prediction results are 164 314 000 and 172 458 000, respectively, using the gray theory. The prediction errors -2.299 0% and -1.595 4% respectively. According to the proposed method, the predicted results are 166.933 million and 176.349 million, respectively. The prediction errors are 0.743 2% and 0.621 9% respectively. It can be seen that the proposed method has higher accuracy and meets the actual needs.