Systematic approach for the prediction of ground-level air pollution (around an industrial port) using an artificial neural network

Aerosol and Air Quality Research

Volumn 14, Issue 1, 2014, Pages 124-134

  Baawain, Mahad S ^a   Al Serihi, Aisha S ^a  

^a SULTAN QABOOS UNIVERSITY   (Oman)

Author keywords

Air pollution; Artificial neural network; Industrial port; Oman

Indexed keywords

AIR POLLUTION PREDICTIONS; AIR QUALITY DATA; AMBIENT AIR QUALITY; DAILY VARIATIONS; INDUSTRIAL PORT; METEOROLOGICAL PARAMETERS; MULTI LAYER PERCEPTRON; OMAN;

AIR POLLUTION; AIR QUALITY; BACKPROPAGATION ALGORITHMS; FORECASTING; INDUSTRY; NEURAL NETWORKS; NITROGEN OXIDES; SULFUR DIOXIDE;

INDUSTRIAL EMISSIONS;

AIR QUALITY; AMBIENT AIR; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; CONCENTRATION (COMPOSITION); HYDROGEN SULFIDE; METEOROLOGY; OXIDE; OZONE; PREDICTION; WIND VELOCITY;

OMAN;

EID: 84893071698     PISSN: 16808584     EISSN: 20711409     Source Type: Journal    
DOI: 10.4209/aaqr.2013.06.0191     Document Type: Article

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