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dc.contributor.authorAlrashedi, Ahmed
dc.contributor.authorAbbod, Maysam
dc.date.accessioned2023-02-20T10:10:20Z
dc.date.available2023-02-20T10:10:20Z
dc.date.issued2022-10-21
dc.identifier.citationADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 11 (2022)
dc.identifier.issn2255-2863
dc.identifier.urihttp://hdl.handle.net/10366/151983
dc.description.abstractIn this paper, we have looked at how easy it is for users in an organisation to be given different roles, as well as how important it is to make sure that the tasks are done well using predictive analytical tools. As a result, ensemble of classification and regression tree link Neural Network was adopted for evaluating the effectiveness of role-based tasks associated with organization unit. A Human Resource Manangement System was design and developed to obtain comprehensive information about their employees' performance levels, as well as to ascertain their capabilities, skills, and the tasks they perform and how they perform them. Datasets were drawn from evaluation of the system and used for machine learning evaluation. Linear regression models, decision trees, and Genetic Algorithm have proven to be good at prediction in all cases. In this way, the research findings highlight the need of ensuring that users tasks are done in a timely way, as well as enhancing an organization's ability to assign individual duties.
dc.format.mimetypeapplication/pdf
dc.publisherEdiciones Universidad de Salamanca (España)
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectneural network
dc.subjectgenetic algorithm
dc.subjectdecision trees
dc.subjectnon-linear model
dc.titleAn Ensemble Classification and Regression Neural Network for Evaluating Role-based Tasks Associated with Organizational Unit
dc.typeinfo:eu-repo/semantics/article


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