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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/13555

Title: Daily streamflow forecasting using simplified rule-based fuzzy logic system
Authors: Mohd Shafiek, Yaacob, Dr.
Hishamuddin, Jamaluddin
Sobri, Harun
Keywords: Fuzzy systems;Rainfall-runoff modelling;Time series forecasting;Training algorithms
Issue Date: Dec-2005
Publisher: The Institution of Engineers, Malaysia
Citation: The Journal of the Institution of Engineers, Malaysia, vol. 66(4), 2005, pages 23-28
Abstract: In this study, a simplified fuzzy logic system with uniform partitions in the input space is proposed for forecasting the daily streamflow of four river systems in Malaysia. The proposed simplified fuzzy logic system was calibrated (trained) using backpropagation (BP) and recursive prediction error (RPE) algorithms. For each catchment, the calibration data set consisted of three consecutive years of daily rainfall and streamflow records. Verifications of the calibrated models were done using the data set of the following year. The performances of the simplified fuzzy logic system and the normal fuzzy logic system are compared, with each model having the same number of adjustable parameters. The results are also compared with the auto-regressive with exogenous input model. This study has shown that the proposed RPE algorithm performed better than the more popular BP algorithm. The results show that all the simplified fuzzy logic system models registered better performance measures for the calibration data sets. However, variable results were obtained for the predictions of the verification data sets.
Description: Link to publisher's homepage at http://www.myiem.org.my/
URI: http://www.myiem.org.my/content/iem_journal_2005-176.aspx
http://hdl.handle.net/123456789/13555
ISSN: 0126-513X
Appears in Collections:IEM Journal

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