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Preview	Issue Date	Title	Author(s)
	2015	Improved PMI-based input variable selection approach for artificial neural network and other data driven environmental and water resource models	Li, X.; Maier, H.; Zecchin, A.
	2015	Using characteristics of the optimisation problem to determine the Genetic Algorithm population size when the number of evaluations is limited	Gibbs, M.; Maier, H.; Dandy, G.
	2015	Improved genetic algorithm optimization of water distribution system design by incorporating domain knowledge	Bi, W.; Dandy, G.; Maier, H.
	2015	Scenario driven optimal sequencing under deep uncertainty	Beh, E.; Maier, H.; Dandy, G.
	2015	A systematic approach to determining metamodel scope for risk-based optimization and its application to water distribution system design	Broad, D.; Dandy, G.; Maier, H.
	2015	Optimal control of total chlorine and free ammonia levels in a water transmission pipeline using artificial neural networks and genetic algorithms	Wu, W.; Dandy, G.; Maier, H.
	2015	Integrating modelling and smart sensors for environmental and human health	Reis, S.; Seto, E.; Northcross, A.; Quinn, N.; Convertino, M.; Jones, R.; Maier, H.; Schlink, U.; Steinle, S.; Vieno, M.; Wimberly, M.
	2015	Improving partial mutual information-based input variable selection by consideration of boundary issues associated with bandwidth estimation	Li, X.; Zecchin, A.; Maier, H.
	2015	Adaptive, multiobjective optimal sequencing approach for urban water supply augmentation under deep uncertainty	Beh, E.; Maier, H.; Dandy, G.
	2015	Assessment of the internal dynamics of the Australian Water Balance Model under different calibration regimes	Li, L.; Lambert, M.; Maier, H.; Partington, D.; Simmons, C.