Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10164
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dc.contributor.authorSajjad, Aisha-
dc.contributor.authorShrivastava, Amit [Guided by]-
dc.contributor.authorSharma, Vipul [Guided by]-
dc.date.accessioned2023-09-30T07:31:01Z-
dc.date.available2023-09-30T07:31:01Z-
dc.date.issued2023-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/10164-
dc.descriptionEnrollment No. 191208en_US
dc.description.abstractThe nature of international business is changing as a result of big data and AI/ML. Today, data is the most important asset for businesses across all sectors. Businesses are utilizing data-driven insights to gain a competitive edge. As a result, machine learning-based data analytics are quickly gaining traction in a variety of industries, creating autonomous systems that assist in human decision-making. In the aviation industry, machine learning algorithms can handle massive amounts of diverse data, eliminating extraneous data points to produce a precise image of each individual aircraft component. Multiple condition-based monitoring and predictive maintenance processes are made more efficient by this feature. Data from several sources, including flight data recorders and logbooks, are used by machine learning for predictive maintenance in the aviation industry.en_US
dc.language.isoen_USen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectAircraftsen_US
dc.subjectData analyticsen_US
dc.subjectMachine learningen_US
dc.subjectAviationen_US
dc.titlePredictive Maintenance of Aircraft using Data Analytics and Machine Learningen_US
dc.typeProject Reporten_US
Appears in Collections:B.Tech. Project Reports

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