Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/41934
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dc.coverage.spatialA fuzzy knowledge based pragmaticApproach to predict optimal routingOn boulevard networken_US
dc.date.accessioned2015-05-20T08:24:12Z-
dc.date.available2015-05-20T08:24:12Z-
dc.date.issued2015-05-20-
dc.identifier.urihttp://hdl.handle.net/10603/41934-
dc.description.abstractTransportation route selection and optimization are intertwined in newlineroad network and these issues remain elusive to both planners and road users newlineThe problems seized upon are an amalgamation as well as interplay of newlinemultiple factors human machine and nature Thus the optimal routing has newlinebecome the uppermost concern of all the road users of the large road networks newlineand the researchers in turn move heaven and earth to get a breakthrough in newlinethe invention of an algorithm that best suits the road user in saving him time newlinecost and distance by making an allowance for the road risk factors both newlinefrequent and non frequent aspects related to road pavement environment newlineand human factors Hence a pragmatic and user friendly stance is attempted in newlinethe thesis newlineConcepts that form the user friendly qualities of road users time newlinecost and distance alone shape the aspirations of the thesis Fuzzy logic is newlineapplied in achieving the above goals since it attempts to solve problems by newlineassigning values to an imprecise spectrum of data in order to arrive at the newlinemost accurate conclusion possible in the same way that humans do newlineThe goal of optimal route selection in road network is attempted newlinewith three atypical approaches The first kind is the hierarchical community newlinemining fuzzy ant dynamic routing on large road networks Hierarchical newlinecommunity structure fuzzy logic and ant colony system are applied in the newlinestudy of the problem of route selection The second approach is the use of newlineDijkstra s fuzzy algorithm in the location of shortest path in large road newlinenetworks using fuzzy parameters The third scheme has a different newlineperspective in route selection with the course of action modeled on code newlinebased community network newlineen_US
dc.format.extentxviii, 142p.en_US
dc.languageEnglishen_US
dc.relationp132-141.en_US
dc.rightsuniversityen_US
dc.titleA fuzzy knowledge based pragmaticApproach to predict optimal routingOn boulevard networken_US
dc.title.alternativeen_US
dc.creator.researcherGeetha Men_US
dc.subject.keywordDijkstra s fuzzy algorithmen_US
dc.subject.keywordTransportation route selectionen_US
dc.description.notereference p132-141.en_US
dc.contributor.guideKadharnawaz G Men_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Science and Humanitiesen_US
dc.date.registeredn.d,en_US
dc.date.completed01/09/2014en_US
dc.date.awarded30/09/2014en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Science and Humanities

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02_certificate.pdf660.24 kBAdobe PDFView/Open
03_abstract.pdf8.59 kBAdobe PDFView/Open
04_acknowledgement.pdf6.63 kBAdobe PDFView/Open
05_content.pdf32.12 kBAdobe PDFView/Open
06_chapter1.pdf58.54 kBAdobe PDFView/Open
07_chapter2.pdf145.46 kBAdobe PDFView/Open
08_chapter3.pdf99.44 kBAdobe PDFView/Open
09_chapter4.pdf141.37 kBAdobe PDFView/Open
10_chapter5.pdf455.62 kBAdobe PDFView/Open
11_chapter6.pdf366.04 kBAdobe PDFView/Open
12_chapter7.pdf447.88 kBAdobe PDFView/Open
13_chapter8.pdf26.24 kBAdobe PDFView/Open
14_reference.pdf31.94 kBAdobe PDFView/Open
15_publication.pdf6.44 kBAdobe PDFView/Open


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