Parametric and artificial intelligence based methods for forecasting short term electricity

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DC Field	Value	Language
dc.contributor.author	Norizan Mohamed	-
dc.date.accessioned	2016-04-29T13:08:52Z	-
dc.date.available	2016-04-29T13:08:52Z	-
dc.date.issued	2011-05	-
dc.identifier.uri	http://hdl.handle.net/123456789/4529	-
dc.description.abstract	Kajian 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.iso	en	en_US
dc.publisher	[Johor]: Universiti Teknologi Malaysia	en_US
dc.subject	TJ 216 .N6 2011	en_US
dc.subject	Norizan Mohamed	en_US
dc.subject	Tesis Universiti Teknologi Malaysia 2011	en_US
dc.title	Parametric and artificial intelligence based methods for forecasting short term electricity	en_US
dc.type	Thesis	en_US
Appears in Collections:	Staff Thesis

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