A comparative study of three neural network forecast combination methods for simulated river flows of different rainfall-runoff models

Hydrological Sciences Journal

Volumn 52, Issue 5, 2007, Pages 896-916

  Shamseldin, Asaad Y ^a   O'Connor, Kieran M ^b   Nasr, Ahmed E ^c  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

^b NATIONAL UNIVERSITY OF IRELAND   (Ireland)

^c UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

Multi layer perceptron; Neural network combination methods; Radial basis function; Rainfall runoff model; River flow simulation; Simple neural network

Indexed keywords

CATCHMENTS; COMPUTER SIMULATION; MULTILAYER NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; RAIN; RIVERS; RUNOFF;

NASH-SUTCLIFFE MODEL; RAINFALL-RUNOFF MODEL; RIVER FLOW SIMULATION;

HYDROLOGY;

ARTIFICIAL NEURAL NETWORK; CATCHMENT; CLIMATE CONDITIONS; COMPUTER SIMULATION; FORECASTING METHOD; PERFORMANCE ASSESSMENT; RAINFALL-RUNOFF MODELING; RIVER FLOW;

EID: 34848868092     PISSN: 02626667     EISSN: None     Source Type: Journal    
DOI: 10.1623/hysj.52.5.896     Document Type: Article

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