Measurement and prediction of ozone levels around a heavily industrialized area: a neural network approach
- 5 February 2001
- journal article
- Published by Elsevier BV in Advances in Environmental Research
- Vol. 5 (1), 47-59
- https://doi.org/10.1016/s1093-0191(00)00042-3
Abstract
No abstract availableKeywords
This publication has 12 references indexed in Scilit:
- An artificial neural network for predicting and optimizing immiscible flood performance in heterogeneous reservoirsComputers & Chemical Engineering, 1998
- A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban areaEnvironmental Pollution, 1996
- A Simple Neural Network for Estimating Emission Rates of Hydrogen Sulfide and Ammonia from Single Point SourcesJournal of the Air & Waste Management Association, 1996
- Short-term ozone forecasting by artificial neural networksAdvances in Engineering Software, 1995
- A neural network-based method for short-term predictions of ambient SO2 concentrations in highly polluted industrial areas of complex terrainAtmospheric Environment. Part B. Urban Atmosphere, 1993
- Urban Air Pollution: State of the ScienceScience, 1989
- Learning representations by back-propagating errorsNature, 1986
- Linear regression analyses of ozone and sulphur dioxide in ambient airScience of The Total Environment, 1986
- Ozone-precursor relationships from EKMA diagramsEnvironmental Science & Technology, 1982
- The carbon-bond mechanism: a condensed kinetic mechanism for photochemical smogEnvironmental Science & Technology, 1980