Multilayer perceptron with Cuckoo search in water level prediction for flood forecasting

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DC Field	Value	Language
dc.contributor.author	Suwannee Phitakwinai	en_US
dc.contributor.author	Sansanee Auephanwiriyakul	en_US
dc.contributor.author	Nipon Theera-Umpon	en_US
dc.date.accessioned	2018-09-05T02:57:14Z	-
dc.date.available	2018-09-05T02:57:14Z	-
dc.date.issued	2016-10-31	en_US
dc.identifier.other	2-s2.0-85007196118	en_US
dc.identifier.other	10.1109/IJCNN.2016.7727243	en_US
dc.identifier.uri	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85007196118&origin=inward	en_US
dc.identifier.uri	http://cmuir.cmu.ac.th/jspui/handle/6653943832/55498	-
dc.description.abstract	© 2016 IEEE. The feed forward multilayer perceptron (MLP) with the Cuckoo search (CS) algorithm, called CS-MLP is implemented to predict 7-hours-ahead water level of the Ping river at the downtown area of Chiang Mai, Thailand. The CS-MLP model prediction performance is compared with the regular multilayer perceptron (MLP) and the results from the previous work. The CS-MLP is the best among them with the mean absolute error on the blind test data set of 6.836 cm.	en_US
dc.subject	Computer Science	en_US
dc.title	Multilayer perceptron with Cuckoo search in water level prediction for flood forecasting	en_US
dc.type	Conference Proceeding	en_US
article.title.sourcetitle	Proceedings of the International Joint Conference on Neural Networks	en_US
article.volume	2016-October	en_US
article.stream.affiliations	Chiang Mai University	en_US
Appears in Collections:	CMUL: Journal Articles

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