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Adaptive multilayer perceptron model for hourly steamflow Hydrograph

Ahmat Nor, Nor Irwan and Mohd Kassim, Amir Hashim and Harun, Sobri Adaptive multilayer perceptron model for hourly steamflow Hydrograph. Universiti Tun Hussein Onn Malaysia.


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The modelling of hydnulic and hydtological prccess€s is imporht in viorw of the marry uscs of uater rcsources suoh as hydropower gpneratioo, inigrtiorl rvcer supply, and flood conuol. Therc arc many prcvious works using tte artifioial noural netwonh (ANN) method for modelling vorious complor non-lincar reluionships of hydr,ologiploc€os€s. Tho ANN is well kmwn as a flexible mathematioal suucnne and has the ability to geoerdiz, perns in imprcoiso or noisy rnd mbiguous input ad ouQut drta scts. In this snvdy, ffc muhi-layor fccdforsad neural network is appliod in fto content of ninfrll-nuofr rnodclling on tho hourly dara of seldcted calchment. The me(hodolog5r is ass€ssod using nultilayor perc.ption (ItrA,P) to pedict hourly nrnoff as a fimction of hourly rainfrll for the S*ngai Bekok catohment (Johc, lrfahyeia). Furdcr, fte rssulb are omparcd barveen ANN and HEC.HMS apProach model. It has b€€n found thd the ANN models show a good genoralization of rainfallrunoffrelationship and is bofior rhqn HEC-HMS model.

Item Type: Other
Uncontrolled Keywords: Artificial Noural Netwost (ANN); Multilarer perceetrc$n p), Rainfall-RunofrModoltin& HEC-HMS
Subjects: T Technology > T Technology (General)
Depositing User: M.Iqbal Zainal A
Date Deposited: 28 Jun 2012 00:45
Last Modified: 28 Jun 2012 00:45
URI: http://eprints.uthm.edu.my/id/eprint/2587
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