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dc.contributor.authorDutta, Ritabanen_US
dc.contributor.authorDas, Aruneemaen_US
dc.contributor.authorAryal, Jagannathen_US
dc.date.accessioned2016-06-25T01:57:02Z
dc.date.available2016-06-25T01:57:02Z
dc.date.issued2016en_US
dc.identifier.otherHPU4160292en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/21672
dc.description.abstractIncreasing Australian bush-fire frequencies over the last decade decision sciencehas indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data.en_US
dc.format.extent11 p.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoenen_US
dc.publisherThe Royal Societyen_US
dc.subjectEarth scienceen_US
dc.subjectArtificial intelligenceen_US
dc.subjectAtmosphericen_US
dc.subjectScienceen_US
dc.subjectEnvironmental scienceen_US
dc.subjectBush-fire frequencyen_US
dc.subjectEnsemblemachineen_US
dc.subjectLearningen_US
dc.subjectBig dataen_US
dc.subjectClimatic shiften_US
dc.titleBig data integration shows Australian bush-fire frequency is increasing significantlyen_US
dc.typeBooken_US
dc.size1.34MBen_US
dc.departmentEducationen_US


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