Short-term traffic flow prediction based on improved wavelet neural network

Author:

Chen Qiuxia,Song Ying,Zhao Jianfeng

Funder

Innovation and Entrepreneurship Project for Overseas High-level Talents of Shenzhen

National Science Foundation Project: Research on Collaborative Innovation System of the Pearl River-Xijiang River Economic Belt under Supply-side Reform

Wuzhou Unviersity Foundation Project: Research on transformation and upgrading of manufacturing industry for the Pearl River-Xijiang River Economic Belt

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference20 articles.

1. Wang Y, Lu Z, Qu Y et al (2016) Improving prediction performance of GPS satellite clock bias based on wavelet neural network[J]. GPS Solut 21(2):1–12

2. Duan H, Xiao X, Lei G et al (2017) Hamiltonian cycles decomposition of two cycles’s composite[J]. J Discrete Math Sci Cryptogr 20(5):1241–1250

3. Yang H-F, Dillon TS, Chen YP (2017) Optimized structure of the traffic flow forecasting model with a deep learning approach[J]. IEEE Trans Neural Netw Learn Syst 28(10):2371–2381

4. He W, Zhong C, Sotelo MA et al (2017) Short-term vessel traffic flow forecasting by using an improved Kalman model[J]. Clust Comput 10:1–10

5. Zhou T, Han G, Xu X et al (2018) A learning-based multimodel integrated framework for dynamic traffic flow forecasting[J]. Neural Process Lett 5:1–24

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