Distributed Modeling in a MapReduce Framework for Data-Driven Traffic Flow Forecasting

Abstract
With the availability of increasingly more new data sources collected for transportation in recent years, the computational effort for traffic flow forecasting in standalone modes has become increasingly demanding for large-scale networks. Distributed modeling strategies can be utilized to reduce the computational effort. In this paper, we present a MapReduce-based approach to processing distributed data to design a MapReduce framework of a...
Paper Details
Title
Distributed Modeling in a MapReduce Framework for Data-Driven Traffic Flow Forecasting
Published Date
Mar 1, 2013
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.