Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/53937
Full metadata record
DC FieldValueLanguage
dc.contributor.authorChompoonoot Kasemseten_US
dc.contributor.authorNisachon Sae-Haewen_US
dc.contributor.authorApichat Sopadangen_US
dc.date.accessioned2018-09-04T10:03:08Z-
dc.date.available2018-09-04T10:03:08Z-
dc.date.issued2014-01-01en_US
dc.identifier.issn16851994en_US
dc.identifier.other2-s2.0-84963955004en_US
dc.identifier.other10.12982/cmujns.2014.0044en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84963955004&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/53937-
dc.description.abstractThis research work aims to develop a forecasting model to predict the quantity of supply of off-season longan using multiple regression technique. There are 23 factors that influence the quantity of supply of off-season longan. Data collection was done in Chiang Mai and Lamphun provinces. The forecasting model based on multiple regression techniques, with enter, forward, backward, and stepwise selection methods were adopted, and these methods yielded mean absolute percentage error (MAPE) values of 18.39%, 25.63%, 21.21%, and 25.63%, respectively. These results demonstrate that multiple regression with the enter selection method is practical to predict the quantity of supply of off-season longan.en_US
dc.subjectMultidisciplinaryen_US
dc.titleMultiple regression model for forecasting quantity of supply of off-season longanen_US
dc.typeJournalen_US
article.title.sourcetitleChiang Mai University Journal of Natural Sciencesen_US
article.volume13en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.