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Results and the potential of Rule-Based Fuzzy Cognitive Maps to predict fisher's behaviour are discussed.
The two have used Google Earth, soil maps and topographical maps to predict the spots where ramps are most likely to grow and to expand the picking rotation.
Since the HVS is sensitive to edges in images, we fuse the saliency and edge maps to predict the visual significance of image pixels for image resizing.
Then the Toolbox retrieves and combines data from the library of advection maps to predict the transport through complex components that combine these geometric features.
In this section we derive maps to predict the network activity in the presence of synaptic plasticity.
The patchy coverage of GBIF data, even over small geographic scales was illustrated by a small scale environmental niche modelling study of Cyclamen [11] that compared data from GBIF with detailed extent of occurrence maps to predict lineage extinction risk.
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Researchers at Johns Hopkins University recently developed a "map" to predict the safety of untested chemicals, using data collected by the European Chemicals Agency.
That's using population trend data and GIS mapping to predict what habitats and species are at greatest risk from climate disruption's inevitable impacts.
This paper aims to investigate the potential of using soil-landscape pattern extracted from a soil map to predict soil distribution at unvisited location.
meet specified geographical distribution and legal restrictions". Beyond the use of techniques like ip mapping to predict geographic locations, some argue that the fundamental architecture of the internet should be augmented so as to preserve and report reliable geography data.
Different inputs such as PU and SU traffic statistics can be mapped to predict throughput through trained neural networks [61].
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