Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55498
Title: Multilayer perceptron with Cuckoo search in water level prediction for flood forecasting
Authors: Suwannee Phitakwinai
Sansanee Auephanwiriyakul
Nipon Theera-Umpon
Keywords: Computer Science
Issue Date: 31-Oct-2016
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.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85007196118&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55498
Appears in Collections:CMUL: Journal Articles

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