Predicting time series of railway speed restrictions with time-dependent machine learning techniques

Expert Systems with Applications

Volumn 40, Issue 15, 2013, Pages 6033-6040

  Fink, Olga ^a   Zio, Enrico ^b,c   Weidmann, Ulrich ^a  

^a ETH ZURICH   (Switzerland)

^b EDF R AND D   (France)

^c POLITECNICO DI MILANO   (Italy)

Author keywords

Binary time series predictions; Conditional restricted Boltzmann machines; Discrete event diagnostic data; Echo state networks; Neural networks; Railway operations disruptions; Speed reductions; Tilting system

Indexed keywords

BINARY TIME SERIES; CONDITIONAL RESTRICTED BOLTZMANN MACHINES; DISCRETE EVENTS; ECHO STATE NETWORKS; RAILWAY OPERATIONS; SPEED REDUCTION; TILTING SYSTEM;

ALGORITHMS; BENCHMARKING; CONJUGATE GRADIENT METHOD; LEARNING SYSTEMS; NEURAL NETWORKS; RAILROAD TRANSPORTATION; RESEARCH;

FORECASTING;

EID: 84878930351     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2013.04.038     Document Type: Article

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