Application of artificial neural networks in the prediction of PM10 levels in thewinter months: A case study in the Tricity Agglomeration, Poland

Atmosphere

Volumn 9, Issue 6, 2018, Pages

  Nidzgorska Lencewicz, Jadwiga ^a  

^a WEST POMERANIAN UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Meteorological parameters; Particulate matter; Prediction; Weather

Indexed keywords

AGGLOMERATION; AIR QUALITY; ATMOSPHERIC TEMPERATURE; CARRIER CONCENTRATION; FORECASTING; MEAN SQUARE ERROR; NEURAL NETWORKS; PARTICLES (PARTICULATE MATTER); WEATHERING; WIND;

COEFFICIENT OF DETERMINATION; INDEX OF AGREEMENTS; MEASUREMENT LOCATIONS; METEOROLOGICAL FACTORS; METEOROLOGICAL PARAMETERS; NEURAL NETWORK MODEL; PARTICULATE MATTER; ROOT MEAN SQUARE ERRORS;

COAL COMBUSTION;

ARTIFICIAL NEURAL NETWORK; CONCENTRATION (COMPOSITION); FORECASTING METHOD; METEOROLOGY; PARTICULATE MATTER; PREDICTION; WEATHER; WINTER;

POLAND [CENTRAL EUROPE];

EID: 85047653946     PISSN: None     EISSN: 20734433     Source Type: Journal    
DOI: 10.3390/atmos9060203     Document Type: Article

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