Forecasting the short-term traffic flow in the intelligent transportation system based on an inertia nonhomogenous discrete gray model

DOI10.1155/2017/3515272zbMath1373.90016OpenAlexW2731400027WikidataQ59142886 ScholiaQ59142886MaRDI QIDQ1674896

Huiming Duan, Xin-ping Xiao, Ling-Ling Pei

Publication date: 26 October 2017

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/3515272

zbMATH Keywords

intelligent transportation systeminertia nonhomogenous discrete gray modelshort-term traffic flow

Mathematics Subject Classification ID

Transportation, logistics and supply chain management (90B06)

Related Items (5)

Application of a novel nonlinear multivariate grey Bernoulli model to predict the tourist income of China ⋮ A novel weighted fractional GM(1,1) model and its applications ⋮ A novel car-following inertia gray model and its application in forecasting short-term traffic flow ⋮ A multimode dynamic short-term traffic flow grey prediction model of high-dimension tensors ⋮ A new GM\((1,1)\) model based on cubic monotonicity-preserving interpolation spline

Cites Work

• Discrete grey forecasting model and its optimization
• On novel grey forecasting model based on non-homogeneous index sequence
• A research on a comprehensive adaptive grey prediction model CAGM(1, N)
• A novel interval grey prediction model considering uncertain information
• Grey systems. Theory and applications.
• Empirical test of a microscopic three-phase traffic theory

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