Application of cellular neural network (CNN) to the prediction of missing air pollutant data

Atmospheric Research

Volumn 101, Issue 1-2, 2011, Pages 314-326

  Şahin, Ülkü Alver ^a   Bayat, Cuma ^b   Uçan, Osman N ^c  

^a ISTANBUL UNIVERSITY   (Turkey)

^b ISTANBUL AREL UNIVERSITY   (Turkey)

^c ISTANBUL AYDIN UNIVERSITY   (Turkey)

Author keywords

Air quality; Cellular Neural Network (CNN); Meteorology; Missing data; Particulate matter (PM); Sulfur dioxide (SO2)

Indexed keywords

ACCURATE PREDICTION; AIR POLLUTANT CONCENTRATIONS; AIR POLLUTANTS; AIR POLLUTION MEASUREMENTS; CNN MODELS; DATA MISSING; DATA SETS; EQUIPMENT FAILURES; ISTANBUL; METEOROLOGICAL PARAMETERS; MISSING DATA; MULTIVARIATE LINEAR REGRESSIONS; OBSERVED DATA; PARTICULATE MATTER (PM); POLLUTANT CONCENTRATION; URBAN CENTERS;

AIR QUALITY; CELLULAR NEURAL NETWORKS; FORECASTING; SULFUR; SULFUR DIOXIDE; WIRELESS NETWORKS;

POLLUTION;

AIR QUALITY; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; CONCENTRATION (COMPOSITION); DATA SET; MULTIVARIATE ANALYSIS; PARTICULATE MATTER; POLLUTION MONITORING; PREDICTION; REGRESSION ANALYSIS; SULFUR DIOXIDE;

EID: 79957929492     PISSN: 01698095     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosres.2011.03.005     Document Type: Article

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