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基于Bagging的交通拥堵预测研究
引用本文:汤志康,王伟智,谈蔚欣.基于Bagging的交通拥堵预测研究[J].集美大学学报(自然科学版),2006,11(2):156-160.
作者姓名:汤志康  王伟智  谈蔚欣
作者单位:福州大学自动化研究所,福建,福州,350002
摘    要:针对交通拥堵原因的多元性及单个神经网络拥堵模型准确率不高的特点,设计了一个以BP经网络为弱学习算法、基于Bagging集成学习方法的交通拥堵预测模型.与单个神经网络模型相比,Bagging后的预测模型具有更加优良的性能,可为市内交通预警决策提供分析与支持。

关 键 词:神经网络集成  交通预测  系统仿真
文章编号:1007-7405(2006)02-0156-05
收稿时间:2005-12-08
修稿时间:2005年12月8日

Study on Congestion Prediction Based on Bagging Arithmetic
TANG Zhi-kang,WANG Wei-zhi,TAN Wei-xin.Study on Congestion Prediction Based on Bagging Arithmetic[J].the Editorial Board of Jimei University(Natural Science),2006,11(2):156-160.
Authors:TANG Zhi-kang  WANG Wei-zhi  TAN Wei-xin
Abstract:Congestion prediction is studied. Congestion prediction needs consider traffic factors and surrounding effects. At present, some researchers have developed the traffic prediction models using single neural network. But it is difficult to improve accuracy and stability of model based on single network. This paper combines many factors and presents a congestion prediction system which based on Bagging. The BP neural network is selected as the weak leaner. Experiments show that the system based on Bagging gets better per- formance than single neural network, and can serve as traffic early warning of decision-making.
Keywords:Bagging
本文献已被 CNKI 维普 万方数据 等数据库收录!
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