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Results 1-10 of 17 (Search time: 0.001 seconds).
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PreviewIssue DateTitleAuthor(s)
2002In-channel phosphorus removal from pasture drainage by water couch (Paspalum paspalodes)Wen, L.; Recknagel, F.; Wetzel, R.G.
2001Adaptive agents simulation of freshwater ecosystemsRecknagel, F.; Ghassemi, F.; White, D.; Caddy, S.; Nakanishi, T.; International Congress on Modelling and Simulation (14th : 2001 : Canberra, A.C.T.)
2001Predicting eutrophication effects in the Burrinjuck Reservoir (Australia) by means of the deterministic model SALMO and the recurrent neural network model ANNAWalter, M.; Recknagel, F.; Carpenter, C.; Bormans, M.
2001Predicting chlorophyll-a in freshwater lakes by hybridising process-based models and genetic algorithmsWigham, P.; Recknagel, F.
2002Comparative application of artificial neural networks and genetic algorithms for multivariate time-series modelling of algal blooms in freshwater lakesRecknagel, F.; Bobbin, J.; Whigham, P.; Wilson, H.
2002Relationships between habitat properties and the occurrence of macroinvertebrates in Queensland streams (Australia) discovered by a sensitivity analysis with artificial neural networksMarshall, J.; Hoang, T.; Choy, S.; Recknagel, F.; Wetzel, R.G.
2001An inductive approach to ecological time series modelling by evolutionary computationWigham, P.; Recknagel, F.
2001WETMOD: A generic wetland ecosystem model for the simulation of floodplain wetlands at the Lower River Murray (South Australia)Cetin, L.; Recknagel, F.; Boumans, R.; Ghassemi, F.; White, D.; Cuddy, S.; Nakanishi, T.; International Congress on Modelling and Simulation (14th : 2001 : Canberra, A.C.T.)
2001Inducing explanatory rules for the prediction of algal blooms by genetic algorithmsBobbin, J.; Recknagel, F.
2001Applications of machine learning to ecological modellingRecknagel, F.