A review of artificial neural network models for ambient air pollution prediction

Environmental Modelling and Software

Volumn 119, Issue , 2019, Pages 285-304

  Cabaneros, Sheen Mclean ^a   Calautit, John Kaiser ^b   Hughes, Ben Richard ^a  

^a UNIVERSITY OF STRATHCLYDE   (United Kingdom)

^b UNIVERSITY OF NOTTINGHAM   (United Kingdom)

Author keywords

Air pollution; Artificial neural networks; Backpropagation algorithm; Forecasting; Multilayer perceptron

Indexed keywords

AIR POLLUTION; BACKPROPAGATION; MULTILAYER NEURAL NETWORKS; MULTILAYERS; NEURAL NETWORKS; STRUCTURAL OPTIMIZATION;

AD HOC APPROACH; AIR POLLUTION FORECASTING; AMBIENT AIR POLLUTION; ARTIFICIAL NEURAL NETWORK MODELS; LONG-TERM FORECASTING; OPTIMAL MODEL STRUCTURES; OXIDES OF NITROGEN; RESEARCH ACTIVITIES;

FORECASTING;

AMBIENT AIR; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; BACK PROPAGATION; FORECASTING METHOD; NITROGEN OXIDES; OZONE; PARTICULATE MATTER; PREDICTION;

EID: 85068167085     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2019.06.014     Document Type: Review

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