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Graeme Dandy
Graeme Dandy
Emeritus Professor of Civil and Environmental Engineering, University of Adelaide
Verified email at adelaide.edu.au
Title
Cited by
Cited by
Year
Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications
HR Maier, GC Dandy
Environmental modelling & software 15 (1), 101-124, 2000
29952000
Genetic algorithms compared to other techniques for pipe optimization
AR Simpson, GC Dandy, LJ Murphy
Journal of water resources planning and management 120 (4), 423-443, 1994
10281994
Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
HR Maier, A Jain, GC Dandy, KP Sudheer
Environmental modelling & software 25 (8), 891-909, 2010
10102010
The use of artificial neural networks for the prediction of water quality parameters
HR Maier, GC Dandy
Water resources research 32 (4), 1013-1022, 1996
8041996
An improved genetic algorithm for pipe network optimization
GC Dandy, AR Simpson, LJ Murphy
Water resources research 32 (2), 449-458, 1996
7601996
Input determination for neural network models in water resources applications. Part 1—background and methodology
GJ Bowden, GC Dandy, HR Maier
Journal of Hydrology 301 (1-4), 75-92, 2005
6932005
Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions
HR Maier, Z Kapelan, J Kasprzyk, J Kollat, LS Matott, MC Cunha, ...
Environmental Modelling & Software 62, 271-299, 2014
6772014
Review of input variable selection methods for artificial neural networks
R May, G Dandy, H Maier
Artificial neural networks-methodological advances and biomedical …, 2011
5012011
Optimal division of data for neural network models in water resources applications
GJ Bowden, HR Maier, GC Dandy
Water resources research 38 (2), 2-1-2-11, 2002
4052002
Non-linear variable selection for artificial neural networks using partial mutual information
RJ May, HR Maier, GC Dandy, TMKG Fernando
Environmental Modelling & Software 23 (10-11), 1312-1326, 2008
3772008
Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling
W Wu, GC Dandy, HR Maier
Environmental Modelling & Software 54, 108-127, 2014
3302014
The effect of internal parameters and geometry on the performance of back-propagation neural networks: an empirical study
HR Maier, GC Dandy
Environmental Modelling & Software 13 (2), 193-209, 1998
2961998
Data splitting for artificial neural networks using SOM-based stratified sampling
RJ May, HR Maier, GC Dandy
Neural Networks 23 (2), 283-294, 2010
2942010
Neural network based modelling of environmental variables: a systematic approach
HR Maier, GC Dandy
Mathematical and Computer Modelling 33 (6-7), 669-682, 2001
2732001
Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river
GJ Bowden, HR Maier, GC Dandy
Journal of Hydrology 301 (1-4), 93-107, 2005
2632005
A hybrid approach to monthly streamflow forecasting: integrating hydrological model outputs into a Bayesian artificial neural network
GB Humphrey, MS Gibbs, GC Dandy, HR Maier
Journal of Hydrology 540, 623-640, 2016
2562016
Estimating residential water demand in the presence of free allowances
G Dandy, T Nguyen, C Davies
Land Economics, 125-139, 1997
2461997
Use of artificial neural networks for modelling cyanobacteria Anabaena spp. in the River Murray, South Australia
HR Maier, GC Dandy, MD Burch
Ecological Modelling 105 (2-3), 257-272, 1998
2401998
An evaluation framework for input variable selection algorithms for environmental data-driven models
S Galelli, GB Humphrey, HR Maier, A Castelletti, GC Dandy, MS Gibbs
Environmental Modelling & Software 62, 33-51, 2014
2372014
Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems
RJ May, GC Dandy, HR Maier, JB Nixon
Environmental Modelling & Software 23 (10-11), 1289-1299, 2008
2322008
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