Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/59918
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dc.contributor.authorChen, Deshun
dc.date.accessioned2014-05-19T06:47:57Z
dc.date.available2014-05-19T06:47:57Z
dc.date.copyright2014en_US
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10356/59918
dc.description.abstractEnergy efficiency analysis of machinery in the industry has become an active topic of research in the field of Computer Science. Many researches have focused on applying data mining knowledge into the energy consumption determination process. The main aim of deploying the data mining techniques in the industry field is to make the real‐time decision which has been proved to be very challenging due to the highly resource‐constrained computing, communicating capacities, and huge volume of fast‐changed data generated by the machine. This work provides an overview of how traditional data mining algorithms are applied for energy consumption analysis. The data is generated from the Injection molding machine.en_US
dc.format.extent61 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Computer science and engineeringen_US
dc.titleData clustering for energy efficiency monitoringen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorNg Wee Keongen_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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