Prediction of daily maximum ground ozone concentration using support vector machine

Environmental Monitoring and Assessment

Volumn 162, Issue 1-4, 2010, Pages 169-176

  Chelani, Asha B ^a  

^a NATIONAL ENVIRONMENTAL ENGINEERING RESEARCH INSTITUTE   (India)

Author keywords

Ground ozone concentration; MLP; MR; Sensitivity analysis; SVM

Indexed keywords

ACCURATE PREDICTION; COMPLEX CHEMICAL REACTIONS; GROUND OZONE CONCENTRATION; LOCAL MINIMUMS; METEOROLOGICAL PARAMETERS; NETWORK PARAMETERS; NEURAL NETWORK MODEL; OVERFITTING; OZONE CONCENTRATION; OZONE PRODUCTION; PHENOMENOLOGICAL MODELS;

ATMOSPHERICS; CONCENTRATION (PROCESS); FORECASTING; GEARS; GRAFTING (CHEMICAL); MULTILAYER NEURAL NETWORKS; OZONE; SENSITIVITY ANALYSIS; SYNTHESIS (CHEMICAL);

SUPPORT VECTOR MACHINES;

OZONE;

ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC CHEMISTRY; MODELING; OZONE; PREDICTION; SENSITIVITY ANALYSIS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMICAL PARAMETERS; CONCENTRATION (PARAMETERS); INDIA; METEOROLOGY; PREDICTION; STATISTICAL MODEL; SUPPORT VECTOR MACHINE;

AIR POLLUTANTS; MODELS, THEORETICAL; OZONE; REGRESSION ANALYSIS;

DELHI; INDIA;

EID: 76449085807     PISSN: 01676369     EISSN: 15732959     Source Type: Journal    
DOI: 10.1007/s10661-009-0785-0     Document Type: Article

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