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dc.contributor.advisorMitchell, Joseph S.B.en_US
dc.contributor.authorLohia, Ashishen_US
dc.contributor.otherDepartment of Computer Scienceen_US
dc.date.accessioned2012-05-15T18:04:57Z
dc.date.available2012-05-15T18:04:57Z
dc.date.issued1-Dec-10en_US
dc.date.submittedDec-10en_US
dc.identifierLohia_grad.sunysb_0771M_10375.pdfen_US
dc.identifier.urihttp://hdl.handle.net/1951/55535
dc.description.abstractUncertain weather conditions is one of the biggest challenges faced by air traffic route management. The US airspace is constructed of virtual freeways and all flights have predetermined routes on which to fly, which have originated over years of work and experience. These flight routes are sometimes marred by bad weather conditions which force the pilots to take on alternative routes. It is not very difficult to come up which these alternates if the conditions are known in advance but the real challenge comes when they come up unexpectedly enroute.Stochastic weather conditions such as turbulance and icing are very difficult to predict. For example the most reliable way to know that turbulance exists in a particular region is throug Pilot Reports. The National Center for Atmospheric Research (NCAR) uses mathematical models to get a rough estimate of these weather conditions. These conditions can be quite severe at times and can badly affect flight conditions resulting in unhappy customers.In this thesis I propose various problems, solutions and future directions of research dealing with stochastic weather conditions. As these conditions are not known with certainty, routes have to be planned which have a high probability of success and are robust to small variations.en_US
dc.description.sponsorshipStony Brook University Libraries. SBU Graduate School in Department of Computer Science. Lawrence Martin (Dean of Graduate School).en_US
dc.formatElectronic Resourceen_US
dc.language.isoen_USen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.en_US
dc.subject.lcshComputer Scienceen_US
dc.titleFinding highly probable(robust) paths in the presence of uncertain weatheren_US
dc.typeThesisen_US
dc.description.advisorAdvisor(s): Joseph S.B. Mitchell. Committee Member(s): Esther M. Arkin; Jie Gao.en_US
dc.mimetypeApplication/PDFen_US


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