If you are experiencing problems downloading PDF or HTML fulltext, our helpdesk recommend clearing your browser cache and trying again. If you need help in clearing your cache, please click here . Still need help? Email email@example.com
< previous issue
next issue >
Artificial neural networks as a tool in ecological modelling, an introduction
Lek, S.; Guegan, J.F.
State-of-the-art of ecological modelling with emphasis on development of structural dynamic models
Applications of the self-organising feature map neural network in community data analysis
Radial basis function networks with partially classified data
Neural network architecture selection: new Bayesian perspectives in predictive modelling - Application to a soil hydrology problem
Vila J.-P.; Wagner, V.; Neveu, P.; Voltz, M.; Lagacherie, P.
Software sensor design based on empirical data
Masson, M.H.; Canu, S.; Grandvalet, Y.; Lynggaard-Jensen, A.
pH modelling by neural networks. Application of control and validation data series in the Middle Loire river
Moatar, F.; Fessant, F.; Poirel, A.
Neural network models to study relationships between lead concentration in grasses and permanent urban descriptors in Athens city (Greece)
Dimopoulos, I.; Chronopoulos, J.; Chronopoulou-Sereli, A.; Lek, S.
Support vector machines for optimal classification and spectral unmixing
Brown, M.; Gunn, S.R.; Lewis, H.G.
Water and carbon fluxes above European coniferous forests modelled with artificial neural networks
van Wijk, M.T.; Bouten, W.
Modelling primary production in a coastal embayment affected by upwelling using dynamic ecosystem models and artificial neural networks
Barciela, R.M.; Garca, E.; Fernandez, E.
Developing an empirical model of phytoplankton primary production: a neural network case study
Scardi, M.; Harding, L.W.
Wedding connectionist and algorithmic modelling towards forecasting Caulerpa taxifolia development in the north-western Mediterranean sea
Aussem, A.; Hill, D.
Applying artificial neural network methodology to ocean color remote sensing
Gross, L.; Thiria, S.; Frouin, R.
Predictive models of collembolan diversity and abundance in a riparian habitat
Lek-Ang, S.; deharveng, L.; Lek, S.
Prediction of response of zooplankton biomass to climatic and oceanic changes
Aoki, I.; Komatsu, T.; Hwang, K.
Modelling water quality, bioindication and population dynamics in lotic ecosystems using neural networks
Schleiter, I.M.; Borchardt, D.; Wagner, R.; Dapper, T.; Schmidt, K.; Schmidt, H.; Werner, H.
Individual-based modelling of fishermen search behaviour with neural networks and reinforcement learning
Jules Dreyfus-Leon, M.
The use of artificial neural networks to assess fish abundance and spatial occupancy in the littoral zone of a mesotrophic lake
Brosse, S.; Guegan, J.; Tourenq, J.; Lek, S.
Microsatellites and artificial neural networks: tools for the discrimination between natural and hatchery brown trout (Salmo trutta, L.) in Atlantic populations
Aurelle, D.; Lek, S.; Giraudel, J.; Berrebi, P.
Predicting fish yield of African lakes using neural networks
Lae, R.; Lek, S.; Moreau, J.
Comparing discriminant analysis, neural networks and logistic regression for predicting species distributions: a case study with a Himalayan river bird
Manel, S.; Dias, J.; Ormerod, S.J.
Use of artificial neural networks for predicting rice crop damage by greater flamingos in the Camargue, France
Tourenq, C.; Aulagnier, S.; Mesleard, F.; Durieux, L.; Johnson, A.; Gonzalez, G.; Lek, S.