Prediction of air pollutants concentration based on an extreme learning machine: The case of Hong Kong

International Journal of Environmental Research and Public Health

Volumn 14, Issue 2, 2017, Pages

  Zhang, Jiangshe ^a   Ding, Weifu ^a,b  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b BEIFANG UNIVERSITY OF NATIONALITIES   (China)

Author keywords

Air pollution; Back propagation; Extreme learning machine; Feed forward neural network; Prediction

Indexed keywords

AIR QUALITY; ALGORITHM; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; BACK PROPAGATION; CONCENTRATION (COMPOSITION); MACHINE LEARNING; POLLUTANT SOURCE; POLLUTION MONITORING; PREDICTION; URBAN POLLUTION;

AIR POLLUTANT; AIR QUALITY; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CITY; ECONOMIC ASPECT; EXPERIMENTAL MODEL; HONG KONG; MACHINE LEARNING; MONITORING; NERVOUS SYSTEM; PREDICTION; VELOCITY; AIR POLLUTION; ALGORITHM; ANALYSIS; ENVIRONMENTAL MONITORING; FORECASTING; PROCEDURES; STATISTICS AND NUMERICAL DATA;

CHINA; HONG KONG;

AIR POLLUTANT;

AIR POLLUTANTS; AIR POLLUTION; ALGORITHMS; CITIES; ENVIRONMENTAL MONITORING; FORECASTING; HONG KONG; NEURAL NETWORKS (COMPUTER);

EID: 85011096722     PISSN: 16617827     EISSN: 16604601     Source Type: Journal    
DOI: 10.3390/ijerph14020114     Document Type: Article

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