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Artificial neural networks (ANNs) are non-linear mapping structures based on the function of the human brain. They have been shown to be universal and highly flexible function approximators for any data. These make powerful tools for models, especially when the underlying data relationships are unknown. In this reason, the international workshop on the(More)
The present study aims at assessing the current situation of the heavy metal contaminated River Lot (SW France). Several fish species were captured in October 1987 and 2007 at three sampling sites. The concentration of copper, zinc, cadmium and lead were quantified in fish muscle and liver as well as in environmental samples (water, sediment, moss). The(More)
Processes governing patterns of richness of riverine fish species at the global level can be modelled using artificial neural network (ANN) procedures. These ANNs are the most recent development in computer-aided identification and are very different from conventional techniques 1,2. Here we use the potential of ANNs to deal with some of the persistent(More)
The method of neural networks was tested for its ability to assign individuals on the basis of their multilocus genotypes, using a data collection of 430 honeybees and 8 microsatellite loci. This data set includes various taxonomical levels (populations within the same subspecies, various subspecies belonging to the same evolutionary lineage, and the 3(More)
In European freshwater, cyprinid fish may be heavily infected by plerocercoids of the pseudophyllidea cestode Ligula intestinalis (L.). During their development, these parasites grow rapidly to a large size in the fish's body cavity, characteristically distending the abdomen. In this study, the influence of this tapeworm on roach (Rutilus rutilus L.)(More)
To provide an efficient and running analytical tool to strawberry plant breeders who have to characterize and compare the aromatic properties of new cultivars to those already known, a HS-SPME/GC-MS analysis method has been coupled with a statistical treatment method issued from the current development of artificial neuron networks (ANN), and more(More)
Parasite species with global distributions and complex life cycles offer a rare opportunity to study alternative mechanisms of speciation and evolution in a single model. Here, genealogy and genetic structure, with respect to geography and fish host preference, have been analyzed for Ligula intestinalis, a tapeworm affecting freshwater fish. The data(More)
Rostrum dace (Leuciscus leuciscus burdigalensis) from the River Viaur were found to be infested with the ectoparasite Tracheliastes polycolpus (Copepoda: Lernaeopodidae). Samples from five study sites along the river revealed different patterns of parasite infestation. Heavily infested fish were found at the upper study sites whereas much lower infestation(More)
In most applications of the multilayer perceptron (MLP) the main objective is to maximize the generalization ability of the network. We show that this ability is related to the sensitivity of the output of the MLP to small input changes. Several criteria have been proposed for the evaluation of the sensitivity. We propose a new index and present a way for(More)