摘要
为解决一般预测方法要求原始数据量较大 ,而无检测器交叉口所能获得的交通流量数据又非常有限的矛盾 ,提出了利用灰色系统理论预测无检测器交叉口交通流量的方法 ,并建立了一种新的自适应GM( 1 ,1 )模型 .利用编制的计算机程序对常熟市无检测器交叉口交通流量进行预测计算分析 ,结果表明自适应GM( 1 ,1 )模型可以根据有限的交通流量数据进行预测 ,且预测精度较之全数据GM( 1 ,1 )模型有显著提高 .实践证明 。
Conventional prediction methods require large number of samples while traffic flow data at non-detector intersections is very limited. To solve this problem a new self-adapting GM (1,1) model to predict traffic flow at non-detector intersections using the grey theory is proposed. The practical implementation of the new model through calculating program compiled was accomplished by a case study in Changshu, Jiangsu province. Results show that self-adapting GM (1,1) can achieve much better prediction accuracy than that of total data GM (1,1).
出处
《东南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2002年第2期256-258,共3页
Journal of Southeast University：Natural Science Edition
基金
公安部"九五"重点科技攻关资助项目 (96 A15 0 2 0 4)
