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dc.contributor.authorNorizan Mohamed-
dc.date.accessioned2016-04-29T13:08:52Z-
dc.date.available2016-04-29T13:08:52Z-
dc.date.issued2011-05-
dc.identifier.urihttp://hdl.handle.net/123456789/4529-
dc.description.abstractKajian ini bertujuan membina model terbaik bagi penelahan tenaga elektrik di Malaysia. Untuk mendapatkan model terbaik, data setiap setengah jam tenaga elektrik bagi tempoh setahun digunakan dengan peratus purata ralat mutlak (PPRM) sebagai ukuran kejituan telahan. Tiga kaedah iaitu model Purata Bergerak Terkamir Autoregresi Dua Musim (PBTADM), model rangkaian neural pelbagai lapis suap hadapan dan model gabungan dipertimbangkan.en_US
dc.language.isoenen_US
dc.publisher[Johor]: Universiti Teknologi Malaysiaen_US
dc.subjectTJ 216 .N6 2011en_US
dc.subjectNorizan Mohameden_US
dc.subjectTesis Universiti Teknologi Malaysia 2011en_US
dc.titleParametric and artificial intelligence based methods for forecasting short term electricityen_US
dc.typeThesisen_US
Appears in Collections:Staff Thesis

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