An Improved Fuzzy Neural Network for Traffic Speed Prediction Considering Periodic Characteristic

Volume: 18, Issue: 9, Pages: 2340 - 2350
Published: Sep 1, 2017
Abstract
This paper proposes a new method in construction fuzzy neural network to forecast travel speed for multi-step ahead based on 2-min travel speed data collected from three remote traffic microwave sensors located on a southbound segment of a fourth ring road in Beijing City. The first-order Takagi-Sugeno system is used to complete the fuzzy inference. To train the evolving fuzzy neural network (EFNN), two learning processes are proposed. First, a...
Paper Details
Title
An Improved Fuzzy Neural Network for Traffic Speed Prediction Considering Periodic Characteristic
Published Date
Sep 1, 2017
Volume
18
Issue
9
Pages
2340 - 2350
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.