Ecological Informatics: Current Scope and Future Directions

Author:

Recknagel Friedrich

Publisher

Springer Berlin Heidelberg

Reference58 articles.

1. Aoki, I. and T. Komatsu, 1997. Analysis and prediction of the fluctuation of sardine abundance using a neural network. Oceanologica Acta 20, 1, 81-88.

2. Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D., 1997. Genetic Programming: An Introduction on the Automatic Evolution of Computer Programs and its Applications. Morgan Kaufmann.

3. Cao, H., Recknagel, F, Welk, A. , Kim, B. and N. Takamura, 2006. Hybrid Evolutionary Algorithm for Rule Set Discovery in Time-Series Data to Forecast and Explain Algal Population Dynamics in Two Lakes Different in Morphome try and Eutrophication. In: Recknagel, F. (ed.), 2006. Ecological Informatics. 2ndEdition. Springer-Verlag Berlin, Heidelberg, New York, 330-342.

4. Cao, H. and F. Recknagel, 2009. Hybridisation of process-based ecosystem models with evolutionary algorithms: Multi-objective optimisation of process representations and parameters of the lake simulation library SALMO-OO. In:Jorgensen, S.E., Chon, T.S. and F. Recknagel, (editors), 2009. Handbook of Ecological Modelling and Informatics, WIT Press, Southampton, Chapter 10, 169-185.

5. Capcarrere, M. Tettamanzi, A. Tomassini, M. and M. Sipper, 1998. Studying parallel evolutionary algorithms: The cellular Programming Case. In: Eiben et al. (editors), 1998. Parallel Problem Solving from Nature V. Springer-Verlag, New York, 573-582.

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