Forecasting PM 10 in metropolitan areas: Efficacy of neural networks

Environmental Pollution

Volumn 163, Issue , 2012, Pages 62-67

  Fernando, H J S ^a   Mammarella, M C ^b   Grandoni, G ^b   Fedele, P ^b   Di Marco, R ^b   Dimitrova, R ^a   Hyde, P ^c  

^a UNIVERSITY OF NOTRE DAME   (United States)

^b ENEA   (Italy)

^c ARIZONA STATE UNIVERSITY   (United States)

Author keywords

Air quality prediction; Human health warnings; Neural network

Indexed keywords

AIR QUALITY PREDICTION; ARIZONA; ARTIFICIAL NEURONS; AUTOMATED MONITORING; HISTORIC DATA; HUMAN HEALTH; METROPOLITAN AREA; MONITORING SITES; PARTICULATE MATTER; PHOTOCHEMICAL AIR QUALITY MODELS; PHOTOCHEMICAL MODELS; PREDICTIVE TOOLS; REGULATORY MANAGEMENT; STOCHASTIC METHODS;

AIR QUALITY; FORECASTING;

NEURAL NETWORKS;

AIR QUALITY; ARTIFICIAL NEURAL NETWORK; DECISION MAKING; FORECASTING METHOD; METROPOLITAN AREA; PARTICULATE MATTER; PUBLIC HEALTH; STOCHASTICITY;

AIR MONITORING; AIR QUALITY; ARTICLE; CONTROLLED STUDY; FORECASTING; NERVE CELL NETWORK; PARTICULATE MATTER; PHOTOCHEMISTRY; PREDICTION; STOCHASTIC MODEL; UNITED STATES; URBAN AREA; AIR POLLUTANT; AIR POLLUTION; ARTIFICIAL NEURAL NETWORK; ATMOSPHERE; CHEMICAL MODEL; CHEMISTRY; CITY; ENVIRONMENTAL MONITORING; METHODOLOGY; PARTICLE SIZE; STATISTICS;

ARIZONA; PHOENIX; UNITED STATES;

AIR POLLUTANTS; AIR POLLUTION; ATMOSPHERE; CITIES; ENVIRONMENTAL MONITORING; FORECASTING; MODELS, CHEMICAL; NEURAL NETWORKS (COMPUTER); PARTICLE SIZE; PARTICULATE MATTER; STATISTICS AS TOPIC;

EID: 84855514053     PISSN: 02697491     EISSN: 18736424     Source Type: Journal    
DOI: 10.1016/j.envpol.2011.12.018     Document Type: Article

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