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- W2077809788 abstract "Recently, kernel-based Machine Learning methods have gained greatpopularity in many data analysis and data mining fields: patternrecognition, biocomputing, speech and vision, engineering, remotesensing etc. The paper describes the use of kernel methods to approachthe processing of large datasets from environmental monitoring networks.Several typical problems of the environmental sciences and theirsolutions provided by kernel-based methods are considered: classificationof categorical data (soil type classification), mapping of environmentaland pollution continuous information (pollution of soil by radionuclides),mapping with auxiliary information (climatic data from Aral Sea region).The promising developments, such as automatic emergency hot spotdetection and monitoring network optimization are discussed as well." @default.
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- W2077809788 date "2007-12-30" @default.
- W2077809788 modified "2023-09-26" @default.
- W2077809788 title "Mapping of environmental data using kernel-based methods" @default.
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- W2077809788 doi "https://doi.org/10.3166/geo.17.309-331" @default.
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