A novel three-step procedure to forecast the inspection volume

Transportation Research Part C: Emerging Technologies

Volumn 56, Issue , 2015, Pages 393-414

  Ruiz Aguilar, J J ^a   Turias, I J ^a   Jimenez Come M J ^a  

^a UNIVERSITY OF CÁDIZ   (Spain)

Author keywords

Artificial Neural Networks (ANNs); Inspection forecasting; Seasonal auto regressive integrated moving averages (SARIMA); Self organizing maps (SOM)

Indexed keywords

AUTOREGRESSIVE MOVING AVERAGE MODEL; CLUSTER ANALYSIS; CONFORMAL MAPPING; DECISION MAKING; FORECASTING; INSPECTION; PREDICTIVE ANALYTICS; TIME SERIES;

AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE; CLUSTERING TECHNIQUES; DECISION MAKING TOOL; FORECASTING METHODS; HYBRID PREDICTION MODELS; PREDICTION TECHNIQUES; STATISTICAL PROPERTIES; TIME SERIES PREDICTION;

SELF ORGANIZING MAPS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; DECISION MAKING; FORECASTING METHOD; FREIGHT TRANSPORT; REGRESSION ANALYSIS; TIME SERIES ANALYSIS; TRAFFIC CONGESTION; TRANSPORTATION SYSTEM;

EID: 84955327395     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2015.04.024     Document Type: Article

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