Artificial neural network models for daily PM10 air pollution index prediction in the urban area of Wuhan, China

Environmental Engineering Science

Volumn 28, Issue 5, 2011, Pages 357-363

  Wu, Shengjun ^a   Feng, Qi ^a   Du, Yun ^a   Li, Xiaodong ^a  

^a Wuhan National Laboratory for Optoelectronics   (China)

Author keywords

Artificial neural network; dust storm; Elman; recurrent neural network

Indexed keywords

ACCURACY RATE; AIR POLLUTION INDEX; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; COEFFICIENT OF DETERMINATION; DUST STORM; ELMAN; FORECAST MODEL; LEADTIME; MEAN ABSOLUTE ERROR; MONITORING STATIONS; NORTHERN CHINA; PARTICULATE MATTER; PREDICTION ACCURACY; ROOT MEAN SQUARE ERRORS; URBAN AREAS; WUHAN , CHINA;

AIR QUALITY; DUST; FORECASTING; POLLUTION; RECURRENT NEURAL NETWORKS; TIME SERIES;

STORMS;

AIR POLLUTION INDICATOR; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHINA; COMPARATIVE EFFECTIVENESS; DUST AND DUST RELATED PHENOMENA; PARTICULATE MATTER; PREDICTIVE VALUE; TIME SERIES ANALYSIS; URBAN AREA;

EID: 79955578106     PISSN: 10928758     EISSN: None     Source Type: Journal    
DOI: 10.1089/ees.2010.0219     Document Type: Article

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