Neural network modelling of Baltic zooplankton abundances
This data product is a series of gridded abundance maps for 40 zooplankton species from 2007 to 2013 in the Baltic Sea, based on a neural network analysis. As input data a combination of EMODnet Biology datasets were used, together with the environmental variables dissolved oxygen, salinity, temperature, chlorophyll concentration bathymetry and the distance from coast. Additionally the position (latitude and longitude) and the year are provided to the neural network. DIVAnd (n-dimensional Data-Interpolating Variational Analysis) and the neural network library Knet were used in this analysis.
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Université de Liège |
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Deltares |
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Conformance of this metadata set with the Technical Guidance for the implementation of INSPIRE dataset and service metadata based on ISO/TS 19139:2007 was not evaluated |
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Conformance of this data set with the INSPIRE Implementing Rules for the interoperability of spatial data sets and services was not evaluated |
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