Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/4718
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dc.contributor.authorMohamed, Ayman Ezzaldeen
dc.contributor.authorSupervisor - Howida Ali Abd Elgader
dc.date.accessioned2014-04-29T12:01:36Z
dc.date.available2014-04-29T12:01:36Z
dc.date.issued2013-11-25
dc.identifier.citationMohamed,Ayman Ezzaldeen.Detection Association Rules in Sudanese Company for Electricity Distribution Ltd Data-Set/ Ayman Ezzaldeen Mohamed ؛ Howida Ali Abd Elgader.-Khartoum : sudan university of science and technology, computer science,2013.-62p:ill;28cm.-M.Sc.en_US
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/4718
dc.descriptionThesisen_US
dc.description.abstractElectrical failure in the management companies is one of the most difficult administrative work, This is because the imbalance which leads to poor service, customer mump and the increase in the volume of data without the benefit of it; is one of the disadvantages of the use of computers, one of the modern techniques in data mining to extract knowledge, and new relationships with the assistance of decision-makers in corporate management. The objective of this research is to use the failures dataset of the following areas (Khartoum, Khartoum North, and Omdurman) and one of the mining techniques is applied on it; it’s association rules with two different algorithms. The research results have shown that there is a set of relationships which is important, and linked between time, station and the type of failure.en_US
dc.description.sponsorshipsudan university of science and technologyen_US
dc.language.isoenen_US
dc.publisherSudan University of Science and Technologyen_US
dc.subjectDetectionen_US
dc.subjectAssociation Rulesen_US
dc.subjectData-Seten_US
dc.titleDetection Association Rules in Sudanese Company for Electricity Distribution Ltd Data-Seten_US
dc.title.alternativeاكتشاف قواعد الأرتباط في مجموعة بيانات الشركة السودانية لتوزيع الكهرباء المحدودةen_US
dc.typeThesisen_US
Appears in Collections:Masters Dissertations : Computer Science and Information Technology

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