Graeme C. Dandy

Overview

Best Publications

• Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications

  Holger R. Maier;Graeme C. Dandy

  2958
  Citations

• Genetic algorithms compared to other techniques for pipe optimization

  Angus R. Simpson;Graeme C. Dandy;Laurence J. Murphy

  1005
  Citations

• Review: Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions

  Holger R. Maier;Ashu Jain;Graeme C. Dandy;K. P. Sudheer

  998
  Citations

• The Use of Artificial Neural Networks for the Prediction of Water Quality Parameters

  Holger R. Maier;Graeme C. Dandy

  805
  Citations

• Evolutionary algorithms and other metaheuristics in water resources

  H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat

  767
  Citations

• An Improved Genetic Algorithm for Pipe Network Optimization

  Graeme C. Dandy;Angus R. Simpson;Laurence J. Murphy

  749
  Citations

• Input determination for neural network models in water resources applications. Part 1—background and methodology

  Gavin J. Bowden;Graeme C. Dandy;Holger R. Maier

  682
  Citations

• Review of Input Variable Selection Methods for Artificial Neural Networks

  Robert May;Graeme Dandy;Holger Maier

  443
  Citations

• Optimal division of data for neural network models in water resources applications

  Gavin J. Bowden;Holger R. Maier;Graeme C. Dandy

  395
  Citations

• Non-linear variable selection for artificial neural networks using partial mutual information

  Robert J. May;Holger R. Maier;Graeme C. Dandy;T.M.K. Gayani Fernando

  385
  Citations

• Review: 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

  Wenyan Wu;Graeme C. Dandy;Holger R. Maier

  337
  Citations

• The effect of internal parameters and geometry on the performance of back-propagation neural networks: an empirical study

  Holger R. Maier;Graeme C. Dandy

  299
  Citations

• Data splitting for artificial neural networks using SOM-based stratified sampling.

  Robert J. May;Holger R. Maier;Graeme C. Dandy

  275
  Citations

• A hybrid approach to monthly streamflow forecasting: Integrating hydrological model outputs into a Bayesian artificial neural network

  Greer B. Humphrey;Matthew S. Gibbs;Graeme C. Dandy;Holger R. Maier

  267
  Citations

• Neural network based modelling of environmental variables: A systematic approach

  H. R. Maier;G. C. Dandy

  265
  Citations

• Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river

  Gavin J. Bowden;Holger R. Maier;Graeme C. Dandy

  258
  Citations

• Use of artificial neural networks for modelling cyanobacteria Anabaena spp. in the River Murray, South Australia

  Holger R Maier;Graeme C Dandy;Michael D Burch

  236
  Citations

• An evaluation framework for input variable selection algorithms for environmental data-driven models

  Stefano Galelli;Greer B. Humphrey;Holger R. Maier;Andrea Castelletti

  232
  Citations

• Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems

  Robert J. May;Graeme C. Dandy;Holger R. Maier;John B. Nixon

  220
  Citations

• Water Distribution System Optimization Using Metamodels

  D. R. Broad;G. C. Dandy;H. R. Maier

  218
  Citations

• Selection of input variables for data driven models: An average shifted histogram partial mutual information estimator approach

  T.M.K.G. Fernando;H.R. Maier;G.C. Dandy

  213
  Citations