Runoff forecasting using fuzzy support vector regression

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DC Field	Value	Language
dc.contributor.author	Sopon Wiriyarattanakul	en_US
dc.contributor.author	Sansanee Auephanwiriyakul	en_US
dc.contributor.author	Nipon Theera-Umpon	en_US
dc.date.accessioned	2018-09-10T03:40:28Z	-
dc.date.available	2018-09-10T03:40:28Z	-
dc.date.issued	2008-12-01	en_US
dc.identifier.other	2-s2.0-66749192857	en_US
dc.identifier.other	10.1109/ISPACS.2009.4806713	en_US
dc.identifier.uri	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=66749192857&origin=inward	en_US
dc.identifier.uri	http://cmuir.cmu.ac.th/jspui/handle/6653943832/60272	-
dc.description.abstract	The Runoff forecasting is an important factor in river basin management. In this paper, we use fuzzy support vector machine regression (FSVMR) to predict the Runoff of Yom River at Sukhothai province, Thailand. The results show that the FSVMR is a suitable method in forecasting Runoff.	en_US
dc.subject	Computer Science	en_US
dc.subject	Social Sciences	en_US
dc.title	Runoff forecasting using fuzzy support vector regression	en_US
dc.type	Conference Proceeding	en_US
article.title.sourcetitle	2008 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2008	en_US
article.stream.affiliations	Chiang Mai University	en_US
Appears in Collections:	CMUL: Journal Articles

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