To efficiently extract implicit patterns from datasets, data mining methods are beneficial tools for analyzing large and complicated as well as small and scarce data. Despite the great potential of applying data mining methods to complicated data, the appropriate methods remain premature and insufficient. The major aim of this dissertation is to present some data mining methods, along with the real data, as a tool for analyzing the complex behavior of functional data.This may be because of the high SO2 emissions generated within the Ohio River Valley in the Midwest region [30, 44] The mean PM2.5 concentration in the Midwest in 2001 (15.02 I¼g/m3) and 2005 (15.56 I¼g/m3), in particular, exceeds theanbsp;...
|Title||:||Functional Data Analysis for Environmental and Biomedical Problems|
|Publisher||:||ProQuest - 2008|