Multiple measures-based chaotic time series for traffic flow prediction based on Bayesian theory

DOI10.1007/s11071-016-2677-5zbMath1349.90196OpenAlexW2281039876MaRDI QIDQ341650

Xiaozheng He, Xiao Jiang, Yinguo Li, Srinivas Peeta, Taixiong Zheng, Yongfu Li, Hao Zhu

Publication date: 16 November 2016

Published in: Nonlinear Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11071-016-2677-5

zbMATH Keywords

Bayesian estimationchaos theorytraffic flowRBF neural networkmulti-measure time seriesphase space reconstruction

Mathematics Subject Classification ID

Bayesian inference (62F15) Traffic problems in operations research (90B20) Time series analysis of dynamical systems (37M10) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (3)

Short-term traffic volume prediction using GA-BP based on wavelet denoising and phase space reconstruction ⋮ Chaotic oscillations of one-dimensional coupled wave equations with mixed energy transports ⋮ A multimode dynamic short-term traffic flow grey prediction model of high-dimension tensors

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