东南大学学报（自然科学版）2016，Vol.18Issue(3)：651-656,6.DOI:10.3969/j.issn.1001-0505.2016.03.033
基于 ARIMA-SVM 模型的快速公交停站时间组合预测方法
Hybrid dwell time prediction method for bus rapid transit based on ARIMA-SVM model
摘要
Abstract
To explore a reliable dwell time prediction technology through experiments,the physical process of bus rapid transit (BRT)when it stays at the stops is analyzed.Both the longitudinal cor-relation and nonlinear effects from other traffic subsystems are included in this process.Therefore, the dwell time can be divided into the linear and nonlinear parts.Accordingly,autoregressive inte-grated moving average(ARIMA)model and support vector machine (SVM)are adopted to predict these two parts,and the final prediction results are produced by combining the two parts.Thus,the hybrid dwell time prediction method for BRT is established.The dwell time and the relative data gained at two stops in BRT Line 2 in Changzhou are modeled.The results indicate that the hybrid prediction method is effective.Compared with the single ARIMA and SVM models,the hybrid pre-diction method has a sharp decline of the mean absolute error (MAPE)and the mean square error (MSE).Also,the target percent whose prediction error is less than 1 s significantly increases.Fur-thermore,the MAPE,MSE and the target percent can reach 0.62%,4.05 s2 and 96.79%,respec-tively,when training data is enough.关键词
差分自回归/支持向量机/组合预测方法/快速公交/停站时间Key words
difference autoregression/support vector machine(SVM)/hybrid prediction method/bus rapid transit/dwell time分类
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杨敏,丁剑,王炜..基于 ARIMA-SVM 模型的快速公交停站时间组合预测方法[J].东南大学学报（自然科学版）,2016,18(3):651-656,6.基金项目
国家自然科学基金资助项目（51338003，51378120）、国家重点基础研究发展计划（973计划）资助项目（2012CB725402）． （）
