Sovan Lek
Sovan Lek
Professor Ecological Modelling, Fish Ecology, Université Toulouse Paul Sabatier
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Review and comparison of methods to study the contribution of variables in artificial neural network models
M Gevrey, I Dimopoulos, S Lek
Ecological modelling 160 (3), 249-264, 2003
9402003
Artificial neural networks as a tool in ecological modelling, an introduction
S Lek, JF Guégan
Ecological modelling 120 (2-3), 65-73, 1999
8491999
Application of neural networks to modelling nonlinear relationships in ecology
S Lek, M Delacoste, P Baran, I Dimopoulos, J Lauga, S Aulagnier
Ecological modelling 90 (1), 39-52, 1996
7281996
Uncertainty in ensemble forecasting of species distribution
L Buisson, W Thuiller, N Casajus, S Lek, G Grenouillet
Global Change Biology 16 (4), 1145-1157, 2010
4702010
Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters
YS Park, R Céréghino, A Compin, S Lek
Ecological modelling 160 (3), 265-280, 2003
3772003
Energy availability and habitat heterogeneity predict global riverine fish diversity
JF Guégan, S Lek, T Oberdorff
Nature 391 (6665), 382-384, 1998
3691998
A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination
JL Giraudel, S Lek
Ecological Modelling 146 (1-3), 329-339, 2001
3622001
Conservation strategies for endemic fish species threatened by the Three Gorges Dam
YS PARK, J Chang, S Lek, W Cao, S Brosse
Conservation biology 17 (6), 1748-1758, 2003
2782003
Climate change hastens the turnover of stream fish assemblages
LËT Buisson, W Thuiller, S Lek, PUY Lim, GËL Grenouillet
Global Change Biology 14 (10), 2232-2248, 2008
2612008
Artificial neuronal networks: application to ecology and evolution
S Lek, JF Guégan
Springer Science & Business Media, 2012
2292012
Ensemble modelling of species distribution: the effects of geographical and environmental ranges
G Grenouillet, L Buisson, N Casajus, S Lek
Ecography 34 (1), 9-17, 2011
2092011
Use of some sensitivity criteria for choosing networks with good generalization ability
Y Dimopoulos, P Bourret, S Lek
Neural Processing Letters 2 (6), 1-4, 1995
1971995
Neural network models to study relationships between lead concentration in grasses and permanent urban descriptors in Athens city (Greece)
I Dimopoulos, J Chronopoulos, A Chronopoulou-Sereli, S Lek
Ecological modelling 120 (2-3), 157-165, 1999
1731999
Role of some environmental variables in trout abundance models using neural networks
S Lek, A Belaud, P Baran, I Dimopoulos, M Delacoste
Aquatic Living Resources 9 (1), 23-29, 1996
1651996
Hierarchical community classification and assessment of aquatic ecosystems using artificial neural networks
YS Park, TS Chon, IS Kwak, S Lek
Science of the total Environment 327 (1-3), 105-122, 2004
1632004
The use of artificial neural networks to predict the presence of small‐bodied fish in a river
S Mastrorillo, S Lek, F Dauba, A Belaud
Freshwater biology 38 (2), 237-246, 1997
1561997
The use of artificial neural networks to assess fish abundance and spatial occupancy in the littoral zone of a mesotrophic lake
S Brosse, JF Guegan, JN Tourenq, S Lek
Ecological modelling 120 (2-3), 299-311, 1999
1521999
Utilisation of non-supervised neural networks and principal component analysis to study fish assemblages
S Brosse, JL Giraudel, S Lek
Ecological Modelling 146 (1-3), 159-166, 2001
1402001
Applications of artificial neural networks predicting macroinvertebrates in freshwaters
PLM Goethals, AP Dedecker, W Gabriels, S Lek, N De Pauw
Aquatic Ecology 41 (3), 491-508, 2007
1332007
Artificial neural networks as a classification method in the behavioural sciences
D Reby, S Lek, I Dimopoulos, J Joachim, J Lauga, S Aulagnier
Behavioural processes 40 (1), 35-43, 1997
1241997
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Artículos 1–20