| 一种改进的灰色模型在交通量预测中的应用 |
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| 引用本文： | 陈淑燕,陈家胜.一种改进的灰色模型在交通量预测中的应用[J].公路交通科技,2004,21(2):80-83. |
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| 作者姓名： | 陈淑燕 陈家胜 |
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| 作者单位： | 南京师范大学江苏省光电重点实验室,江苏,南京,210097 |
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| 摘 要： | GM(1,1)模型是灰色系统理论中的核心,已经得到广泛应用。一种改进GM(1,1)模型无论用于拟合或预测,其结果都明显优于常规GM(1,1)模型。结合遗传算法和最小二乘法获得该模型的待定参数,对改进的GM(1,1)模型给出了一种新的求解方法。将此改进GM(1,1)模型用于交叉口交通量的预测,预测结果较好。将等维递推和自适应的思想引入改进GM(1,1)模型,可进一步提高该模型的预测精度和实用性。
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| 关 键 词： | 灰色模型 遗传算法 交通量预测 |
| 文章编号： | 1002-0268(2004)02-0080-04 |
| 修稿时间： | 2002年12月9日 |
Application of A Novel Grey Model to Traffic Flow Prediction |
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| CHEN Shu-yan,CHEN Jia-sheng.Application of A Novel Grey Model to Traffic Flow Prediction[J].Journal of Highway and Transportation Research and Development,2004,21(2):80-83. |
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| Authors: | CHEN Shu-yan CHEN Jia-sheng |
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| Abstract: | GM(1,1) model is the kernel of Grey system theory, and it is applied widely in practice. An improved GM(1,1) model can achieve much better results than that of conventional one in fitting or prediction. A novel method to solve this model is proposed by Combined Genetic Algorithm and Least Square method to get its indeterminate coefficients. This model is employed to predict traffic flow with better results. Prediction accuracy and practicability can be further improved by use of equal-dimension recurrence and self-adapting in GM(1,1) model. |
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| Keywords: | Gray model Genetic algorithm Traffic flow prediction |
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