32
J.L. Giraudel . S. Lek
References
Chon TS, Park YS, Moon KH, Cha EY (1996) Patternizing communities by using an
artificial neural network. Ecological Modelling, 90, 69-78
Cen!ghino R, Giraude1 JL, Compin A (2001) Spatial analysis of stream invertebrates
distribution in the Adour-Garonne drainage basin (France), using Kohonen se1f
organizing maps. Ecological Modelling, 146(1-3):-180
Foody GM (1999) Applications of the self-organizing feature map neural-network in
community data-analysis. Ecological Modelling, 120(2-3) 97-107
Giraudel JL, Aurelle D, Lek S (2000) Application of the self-organizing mapping and fuzzy
clustering microsatellite data: how to detect genetic structure in brown trout (Salmo
trutta) populations. In Lek S and Gueguan J F (editors) Artificial Neuronal Networks:
application to ecology and evolution, pages 187-201. Springer, Berlin, Heidelberg
Hämäläinen A (1994) A measure of disorder for the self-organizing map. In Proc. ICNN'94,
Int. Conf. on Neural Networks, pages 659-664, Piscataway, NJ. IEEE Service Center
Kaski S, March E (1997) Data exploration using self-organizing maps. Acta Polytechnica
Scandinavica, Mathematics, Computing and Management in Engineering Series No.
82
Kiviluoto K (1996) Topology preservation in self-organizing maps. In ICNN 96. The 1996
IEEE International Conference on Neural Networks, volume I, pages 294-9. IEEE,
New York, NY, USA
Kohonen T (1982) Analysis of a simple se1f-organizing process. Bio!. Cyb., 44(2)135-140
Kohonen T (1995) Self-Organizing Maps, volume 30 of Springer Series in Information
Sciences. Springer, Berlin, Heide1berg. 362 p
Kraaijveld MA, Mao J, Jain AK (1995) A nonlinear projection method based on Kohonen's
topology preserving maps. IEEE Trans. on Neural Networks, 6(3)548-59
Lek S, Giraudel JL, Guegan JF (2000) Neuronal networks: Algorithms and architectures for
ecologists and evolutionary ecologists. In Lek, S. and Gueguan, J.F., editors, Artificial
Neuronal Networks: application to ecology and evolution, pages 3-27 Springer, Berlin,
Heidelberg.
Lek S, Guegan JF (1999) Artificial neural networks as a tool in ecological modelling, an
introduction. Ecological Modelling, 120(2-3)65-73
Ludwig JA, Reynolds JF (1988) Statistical Ecology, a primer on methods and computing.
John Wiley & Sons
Merkl D, Rauber A (1997) Alternative ways far cluster visualization in self-organizing
maps. In Proceedings of WSOM'97, Workshop on Self-Organizing Maps, Espoo,
Finland, June 4-6, pages 106-111. Helsinki University of Technology, Neural
Networks Research Centre, Espoo, Finland
Miikkulainen R (1990) Script recognition with hierarchical feature maps. Connection
Science, 2, 83-10 1
Orl6ci L (1978) Multivariate Analysis in Vegetation Research. W. Junk, The Hague
Peet RK, Loucks OL (1977) A gradient analysis of southern Wisconsin forests. Ecology,
58,485-499
Ultsch A, Siemon HP (1990) Kohonen's se1f organizing feature maps for exploratory data
analysis. In Proc. INNC'90, Int. Neural Network Conf., pages 305-308, Dordrecht,
Netherlands. Kluwer
J.L. Giraudel . S. Lek
References
Chon TS, Park YS, Moon KH, Cha EY (1996) Patternizing communities by using an
artificial neural network. Ecological Modelling, 90, 69-78
Cen!ghino R, Giraude1 JL, Compin A (2001) Spatial analysis of stream invertebrates
distribution in the Adour-Garonne drainage basin (France), using Kohonen se1f
organizing maps. Ecological Modelling, 146(1-3):-180
Foody GM (1999) Applications of the self-organizing feature map neural-network in
community data-analysis. Ecological Modelling, 120(2-3) 97-107
Giraudel JL, Aurelle D, Lek S (2000) Application of the self-organizing mapping and fuzzy
clustering microsatellite data: how to detect genetic structure in brown trout (Salmo
trutta) populations. In Lek S and Gueguan J F (editors) Artificial Neuronal Networks:
application to ecology and evolution, pages 187-201. Springer, Berlin, Heidelberg
Hämäläinen A (1994) A measure of disorder for the self-organizing map. In Proc. ICNN'94,
Int. Conf. on Neural Networks, pages 659-664, Piscataway, NJ. IEEE Service Center
Kaski S, March E (1997) Data exploration using self-organizing maps. Acta Polytechnica
Scandinavica, Mathematics, Computing and Management in Engineering Series No.
82
Kiviluoto K (1996) Topology preservation in self-organizing maps. In ICNN 96. The 1996
IEEE International Conference on Neural Networks, volume I, pages 294-9. IEEE,
New York, NY, USA
Kohonen T (1982) Analysis of a simple se1f-organizing process. Bio!. Cyb., 44(2)135-140
Kohonen T (1995) Self-Organizing Maps, volume 30 of Springer Series in Information
Sciences. Springer, Berlin, Heide1berg. 362 p
Kraaijveld MA, Mao J, Jain AK (1995) A nonlinear projection method based on Kohonen's
topology preserving maps. IEEE Trans. on Neural Networks, 6(3)548-59
Lek S, Giraudel JL, Guegan JF (2000) Neuronal networks: Algorithms and architectures for
ecologists and evolutionary ecologists. In Lek, S. and Gueguan, J.F., editors, Artificial
Neuronal Networks: application to ecology and evolution, pages 3-27 Springer, Berlin,
Heidelberg.
Lek S, Guegan JF (1999) Artificial neural networks as a tool in ecological modelling, an
introduction. Ecological Modelling, 120(2-3)65-73
Ludwig JA, Reynolds JF (1988) Statistical Ecology, a primer on methods and computing.
John Wiley & Sons
Merkl D, Rauber A (1997) Alternative ways far cluster visualization in self-organizing
maps. In Proceedings of WSOM'97, Workshop on Self-Organizing Maps, Espoo,
Finland, June 4-6, pages 106-111. Helsinki University of Technology, Neural
Networks Research Centre, Espoo, Finland
Miikkulainen R (1990) Script recognition with hierarchical feature maps. Connection
Science, 2, 83-10 1
Orl6ci L (1978) Multivariate Analysis in Vegetation Research. W. Junk, The Hague
Peet RK, Loucks OL (1977) A gradient analysis of southern Wisconsin forests. Ecology,
58,485-499
Ultsch A, Siemon HP (1990) Kohonen's se1f organizing feature maps for exploratory data
analysis. In Proc. INNC'90, Int. Neural Network Conf., pages 305-308, Dordrecht,
Netherlands. Kluwer