Friedrich Recknagel
机构: University of Adelaide, School of Biological Sciences
主页: adelaide.edu.au
每年引用次数
引用次数
引用: 4,745
H-指数: 37
I10-指数 : 92
出版物: 199
Effect of Discharges on the Effectiveness of the Cox Creek Wetland System, South Australia
Nor Azman Kasan , Friedrich Recknage , Justin Brookes , Kane Aldridge
Journal of Environmental Science and Technology 7 ( 5) 281 -293
2014
Modeling Of Algal Blooms In FreshwatersUsing Artificial Neural Networks
M. French , F. Recknagel
WIT Transactions on Ecology and the Environment 6
7
1970
A new design procedure for waste stabilization ponds
S. Schwarz , D. Uhlmann , G. Sandring , F. Recknagel
Journal of Water Pollution Control Federation 55 ( 10) 1252 -1255
8
1983
Use of hybrid EA models for the prediction of chlorophyll-a and phytoplankton functional groups abundance in two shallow lakes
A. Talib , F. Recknagel , H. Cao , D. van der Molen
Institute for Mathematical Research
1
2008
Applied Systems Ecology
F. Recknagel
6
1989
A Generic Artificial Neural Network Model for Short Term Predictions of Algal Blooms in Lakes and Reservoirs
H. Wilson , F. Recknagel
Springer, Berlin, Heidelberg 265 -289
2003
Predictive Rules for Phytoplankton Dynamics in Freshwater Lakes Discovered by Evolutionary Algorithms
J. Bobbin , F. Recknagel
Springer, Berlin, Heidelberg 291 -311
4
2003
Forecasting and explanation of algal dynamics in two shallow lakes by recurrent artificial neural network and hybrid evolutionary algorithm
A. Talib , F. Recknagel , H. Cao , D.T. van der Molen
Mathematics and Computers in Simulation 78 ( 2) 424 -434
6
2008
Elucidation and Prediction of Aquatic Ecosystems by Artificial Neuronal Networks
F. Recknagel , H. Wilson
Springer Berlin Heidelberg 143 -155
24
2000
Assessing the effect of abiotic variables and zooplankton on picocyanobacterial dominance in two tropical mesotrophic reservoirs by means of evolutionary computation.
M.I.A. Rocha , F. Recknagel , R.T. Minoti , V.L.M. Huszar
Water Research 149 120 -129
7
2019
Ecological Informatics By Means Of Neural, EvolutionaryAnd Object-oriented Computation
F. Recknagel , H. Cao
WIT Transactions on State-of-the-art in Science and Engineering 34
3
2009
Ecological Informatics: Current Scope And Feature Areas
F. Recknagel
WIT Transactions on State-of-the-art in Science and Engineering 34
2009
Hybridisation Of Process-based Ecosystem Models WithEvolutionary Algorithms: Multi-objective OptimisationOf Process And Parameter Representations Of The LakeSimulation Library SALMO-OO
H. Cao , F. Recknagel
WIT Transactions on State-of-the-art in Science and Engineering 34
5
2009
Patternising phytoplankton dynamics of two shallow lakes in response to restoration measures by applying non-supervised artificial neural networks
A. Talib , F. Recknagel , D. van der Molen
The Environmentalist 27 ( 1) 195 -205
4
2007
Pattern recognition of grazing dynamics in response to fish removal (Lake Wolderwijd, Netherlands) using non-supervised artificial neural networks
A. Talib , Y. Abu Hasan , F. Recknagel , D. T. van der Molen
Water Pollution IX: Ninth International Conference on Water Pollution: Modelling, Monitoring, and Management, 2008, ISBN 978-1-84564-115-3, pág. 23 111 23 -32
2008
Artificial Neural Network Approach to Unravel and Forecast Algal Population Dynamics of Two Lakes Different in Morphometry and Eutrophication
F. Recknagel , A. Welk , B. Kim , N. Takamura
Springer, Berlin, Heidelberg 325 -345
11
2006
Hybrid Evolutionary Algorithm for Rule Set Discovery in Time-Series Data to Forecast and Explain Algal Population Dynamics in Two Lakes Different in Morphometry and Eutrophication
H. Cao , F. Recknagel , B. Kim , N. Takamura
Springer Berlin Heidelberg 347 -367
30
2006
Ecological Informatics: Overview
F. Recknagel
Encyclopedia of Ecology 1041 -1058
5
2008
Current scope, case studies and future directions of ecological informatics
F. Recknagel
Journal of Environmental Informatics 21 ( 1) 3 -11
10
2013
Response of Microcystis and Stephanodiscus to Alternative Flow Regimes of the Regulated River Nakdong (South Korea) Quantified By Model Ensembles Based on the Hybrid Evolutionary Algorithm (HEA)
F. Recknagel , D.-K. Kim , G.-J. Joo , H. Cao
River Research and Applications 33 ( 6) 949 -958
5
2017