Prediction of air pollutant concentration based on sparse response back-propagation training feedforward neural networks

Environmental Science and Pollution Research

Volumn 23, Issue 19, 2016, Pages 19481-19494

  Ding, Weifu ^a,b   Zhang, Jiangshe ^a   Leung, Yee ^c  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b School of Mathematics and Information   (China)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Air pollution prediction; Artificial neural network; Back propagation; Generalization; Multiple linear regression; Sparse response

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; BACK PROPAGATION; CONCENTRATION (COMPOSITION); ENERGY USE; NEUROLOGY; PREDICTION; REGRESSION ANALYSIS; SPATIOTEMPORAL ANALYSIS;

CHINA; HONG KONG;

AIR POLLUTANT;

AIR POLLUTANT; AIR POLLUTION; ALGORITHM; ANALYSIS; ARTIFICIAL NEURAL NETWORK; ENVIRONMENTAL MONITORING; HONG KONG; HUMAN; METEOROLOGY; PROCEDURES; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

AIR POLLUTANTS; AIR POLLUTION; ALGORITHMS; ENVIRONMENTAL MONITORING; HONG KONG; HUMANS; LINEAR MODELS; METEOROLOGY; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER);

EID: 84978161612     PISSN: 09441344     EISSN: 16147499     Source Type: Journal    
DOI: 10.1007/s11356-016-7149-4     Document Type: Article

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