Neurocomputing techniques to dynamically forecast spatiotemporal air pollution data


Real time monitoring, forecasting and modeling air pollutants’ concentrations in major urban centers is one of the top priorities of all local and national authorities globally. This paper studies and analyzes the parameters related to the problem, aiming in the design and development of an effective machine learning model and its corresponding system… (More)
DOI: 10.1007/s12530-013-9078-5


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