西南交通大学学报2012，Vol.47Issue(2)：285-290,6.DOI:10.3969/j.issn.0258-2724.2012.02.019
基于灰色神经网络的点速度预测模型
Spot Speed Prediction Model Based on Grey Neural Network
摘要
Abstract
To overcome the detecting data error due to the temporal and spatial instability of traffic condition and improve the accuracy of spot speed prediction, a spot speed prediction model based on grey neural network was developed on the basis of grey prediction model and BP(back propagation) neutral network. The model combines the characters of low data demand of grey prediction model and the self-learning and self-adaptive abilities of BP neutral network. It uses field data as output to build different grey prediction models, and then the predicted results are used as inputs to train the BP neural network to obtain the optimized model. Case study shows that compared with those of the traditional grey theory and BP neural network models, the average relative deviation between predicted and field data at 20,40,60 s sampling intervals can decrease 32% on average using the proposed model. Therefore, the proposed model can be used as a basis for traffic condition estimation and travel time prediction.关键词
地点车速/灰色神经网络/灰色系统理论/组合预测Key words
spot speed/ grey neural network/ grey system theory/ combination prediction分类
交通工程引用本文复制引用
吴志周,范宇杰,马万经..基于灰色神经网络的点速度预测模型[J].西南交通大学学报,2012,47(2):285-290,6.基金项目
上海市科技攻关项目(11DZ2291400) （11DZ2291400）
