Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation

Atmospheric Environment

Volumn 107, Issue , 2015, Pages 118-128

  Feng, Xiao ^a   Li, Qi ^a   Zhu, Yajie ^a   Hou, Junxiong ^a   Jin, Lingyan ^a   Wang, Jingjie ^a  

^a PEKING UNIVERSITY   (China)

Author keywords

Air mass trajectory based geographic model; Artificial neural networks; PM2.5 forecasting; Wavelet transformation

Indexed keywords

AIR POLLUTION; AIR QUALITY; BACKPROPAGATION; FORECASTING; MEAN SQUARE ERROR; NEURAL NETWORKS; POLLUTION; TRAJECTORIES; WAVELET DECOMPOSITION; WAVELET TRANSFORMS; WIND;

AIR POLLUTION INDICATORS; AIR-POLLUTION MONITORING STATIONS; BACK PROPAGATION NEURAL NETWORKS; EXPERIMENTAL VERIFICATION; GEOGRAPHIC MODEL; ROOT MEAN SQUARED ERRORS; WAVELET TRANSFORMATIONS; WIND SPEED AND DIRECTIONS;

ATMOSPHERIC MOVEMENTS;

AIR MASS; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; CONCENTRATION (COMPOSITION); FORECASTING METHOD; GEOGRAPHICAL VARIATION; NEW RECORD; PARTICULATE MATTER; POLLUTION MONITORING; TRAJECTORY; WAVELET ANALYSIS;

AIR MASS TRAJECTORY ANALYSIS; AIR POLLUTION; AIR QUALITY; ANALYSIS; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CHINA; FORECASTING; HUMIDITY; METEOROLOGICAL PHENOMENA; PARTICULATE MATTER; PERCEPTRON; POLLUTION MONITORING; PRIORITY JOURNAL; ROOT MEAN SQUARED ERROR; STATISTICAL ANALYSIS; TEMPERATURE; VELOCITY; WAVELET ANALYSIS; WIND; WIND DIRECTION; WIND SPEED;

BEIJING [CHINA]; CHINA; HEBEI; TIANJIN;

EID: 84923017379     PISSN: 13522310     EISSN: 18732844     Source Type: Journal    
DOI: 10.1016/j.atmosenv.2015.02.030     Document Type: Article

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