A new hybrid evolutionary based RBF networks method for forecasting time series: A case study of forecasting emergency supply demand time series

Engineering Applications of Artificial Intelligence

Volumn 36, Issue , 2014, Pages 204-214

  Mohammadi, Reza ^a   Fatemi Ghomi, S M T ^a   Zeinali, Farzad ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Demand forecasting; Evolutionary algorithms; Natural disaster; Radial basis function networks; Time series prediction

Indexed keywords

BENCHMARKING; DISASTERS; EVOLUTIONARY ALGORITHMS; FUNCTIONS; GENETIC ALGORITHMS; MULTILAYER NEURAL NETWORKS; NETWORK ARCHITECTURE; NETWORK LAYERS; PARTICLE SWARM OPTIMIZATION (PSO); RADIAL BASIS FUNCTION NETWORKS; TIME SERIES;

ACCELERATION COEFFICIENTS; ADAPTIVE PARTICLE SWARM OPTIMIZATIONS; DEMAND FORECASTING; HYBRID EVOLUTIONARY ALGORITHM; NATURAL DISASTERS; PRE-MATURE CONVERGENCES; RADIAL BASIS FUNCTION NEURAL NETWORKS; TIME SERIES PREDICTION;

FORECASTING;

EID: 84908152186     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2014.07.022     Document Type: Article

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