基于C-C平均法的高速公路交通流参数非线性混沌辨识

Liao Cheng, J. Yuanhua
{"title":"基于C-C平均法的高速公路交通流参数非线性混沌辨识","authors":"Liao Cheng, J. Yuanhua","doi":"10.1109/EIIS.2017.8298648","DOIUrl":null,"url":null,"abstract":"The transportation system is a complex giant system under a variety of internal and external factors restrict and influence, which makes traffic system showed a strong nonlinearity and uncertainty, and traffic flow is the most intuitive reflect these features. Phase space reconstruction based on the chaos is the necessary steps to analyze the nonlinear characteristics of complex systems. The C-C algorithm that using the correlation integral is an effective way to estimate the parameters of delay time τ and delay time window Tw of phase space reconstruction. Due to the length limited and noise of traffic flow time series, the τ and Tw estimated by C-C method is with volatility. To reduce value deviation, the C — C average algorithm is used in this paper to reconstruct the phase space, and to get the optimal delay time of short-term traffic flow parameters. Then the maximal Lyapunov exponent is calculated by the small-data method, to determine whether the traffic flow time series is chaotic system or not.","PeriodicalId":434246,"journal":{"name":"2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nonlinear chaos identification of traffic flow parameters on expressway based on the C-C average method\",\"authors\":\"Liao Cheng, J. Yuanhua\",\"doi\":\"10.1109/EIIS.2017.8298648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The transportation system is a complex giant system under a variety of internal and external factors restrict and influence, which makes traffic system showed a strong nonlinearity and uncertainty, and traffic flow is the most intuitive reflect these features. Phase space reconstruction based on the chaos is the necessary steps to analyze the nonlinear characteristics of complex systems. The C-C algorithm that using the correlation integral is an effective way to estimate the parameters of delay time τ and delay time window Tw of phase space reconstruction. Due to the length limited and noise of traffic flow time series, the τ and Tw estimated by C-C method is with volatility. To reduce value deviation, the C — C average algorithm is used in this paper to reconstruct the phase space, and to get the optimal delay time of short-term traffic flow parameters. Then the maximal Lyapunov exponent is calculated by the small-data method, to determine whether the traffic flow time series is chaotic system or not.\",\"PeriodicalId\":434246,\"journal\":{\"name\":\"2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIIS.2017.8298648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIIS.2017.8298648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

交通系统是一个受多种内外因素制约和影响的复杂巨系统,这使得交通系统表现出强烈的非线性和不确定性,而交通流正是这些特征最直观的体现。基于混沌的相空间重构是分析复杂系统非线性特性的必要步骤。利用相关积分的C-C算法是估计相空间重构延迟时间τ和延迟时间窗Tw参数的有效方法。由于交通流时间序列的长度限制和噪声,C-C方法估计的τ和Tw具有波动性。为了减少数值偏差,本文采用C - C平均算法重构相空间,得到短期交通流参数的最优延迟时间。然后用小数据法计算最大Lyapunov指数,判断交通流时间序列是否为混沌系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonlinear chaos identification of traffic flow parameters on expressway based on the C-C average method
The transportation system is a complex giant system under a variety of internal and external factors restrict and influence, which makes traffic system showed a strong nonlinearity and uncertainty, and traffic flow is the most intuitive reflect these features. Phase space reconstruction based on the chaos is the necessary steps to analyze the nonlinear characteristics of complex systems. The C-C algorithm that using the correlation integral is an effective way to estimate the parameters of delay time τ and delay time window Tw of phase space reconstruction. Due to the length limited and noise of traffic flow time series, the τ and Tw estimated by C-C method is with volatility. To reduce value deviation, the C — C average algorithm is used in this paper to reconstruct the phase space, and to get the optimal delay time of short-term traffic flow parameters. Then the maximal Lyapunov exponent is calculated by the small-data method, to determine whether the traffic flow time series is chaotic system or not.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信