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Hydrological Sciences Journal Volume 52, 2007 - Issue 1
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Original Articles

Multi-step-ahead neural networks for flood forecasting

Réseaux de neurones à échéances multiples pour la prévision de crue

FI-JOHN CHANG Department of Water Resources & Environmental Engineering, TamKang University, Taipei, Taiwan E-mail: [email protected]
,
YEN-MING CHIANG Department of Water Resources & Environmental Engineering, TamKang University, Taipei, Taiwan E-mail: [email protected]
&
LI-CHIU CHANG Department of Water Resources & Environmental Engineering, TamKang University, Taipei, Taiwan E-mail: [email protected]
Pages 114-130 | Received 25 Sep 2005, Accepted 08 Aug 2006, Published online: 18 Jan 2010

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Crossref
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Crossref
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