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Predicting Pre-monsoon Thunderstorms--A Statistical View through Propositional Logic

dc.contributor.authorChattopadhyay, Surajit
dc.date.accessioned2008-07-02T21:10:37Z
dc.date.available2008-07-02T21:10:37Z
dc.date.issued2002-12-21
dc.identifier.citationChattopadhyay, Surajit. "Predicting Pre-monsoon Thunderstorms--A Statistical View through Propositional Logic." Solstice: An Electronic Journal of Geography and Mathematics, Volume XIII, Number 2. Ann Arbor: Institute of Mathematical Geography, 2002. Persistent URL (URI): http://hdl.handle.net/2027.42/60282en_US
dc.identifier.issn1059-5325
dc.identifier.urihttps://hdl.handle.net/2027.42/60282
dc.description.abstractThunderstorms very close to a monsoon and not so close to a monsoon are considered in this analysis. Some important predictors are considered. Pearson Correlation Coefficient and lag-1 autocorrelation coefficients are calculated to create necessary universes of discourse for propositional logic. The purpose is to make regression analysis more convenient for prediction of the pre-monsoon thunderstorm weather phenomenon.en_US
dc.format.extent181507 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.publisherInstitute of Mathematical Geographyen_US
dc.relation.ispartofseriesSolstice, Volume XIII, Number 2en_US
dc.subjectPredictoren_US
dc.subjectPearsonen_US
dc.titlePredicting Pre-monsoon Thunderstorms--A Statistical View through Propositional Logicen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelGeography and Maps
dc.subject.hlbtoplevelSocial Sciences
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/60282/1/monsoon.pdf
dc.owningcollnameMathematical Geography, Institute of (IMaGe)


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