00957nam a2200265 i 450099100297834970753620021022144507.0960610s1921 fr ||| | fre b11736902-39ule_instLE021FD223879ExLDip. SSSCitaRolland, Romain188792Musiciens d'autrefois :l'opera avant l'opera :L'Orfeo de Luigi Rossi, Lully, Gluck, Gretry, Mozart /Romain Rolland7. edParis :Hachette,1921306 p. ;20 cm.Biblioteque d'HistoireCritica musicaleMusicisti.b1173690227-04-1724-10-02991002978349707536LE021FD MUS16A141LE021FD-4188le023Fondo D'Amico-E0.00-no 00000.i1197681024-10-02Musiciens d'autrefois306637UNISALENTOle02110-06-96ma -frefr 0104141nam 22006495 450 991048418620332120200706135036.03-030-00238-110.1007/978-3-030-00238-1(CKB)4100000006098165(DE-He213)978-3-030-00238-1(MiAaPQ)EBC5921776(PPN)258847719(PPN)243768648(EXLCZ)99410000000609816520181113d2019 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierArtificial Intelligent Methods for Handling Spatial Data Fuzzy Rulebase Systems and Gridded Data Problems /by Jörg Verstraete1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (XVI, 135 p. 53 illus., 46 illus. in color.) Studies in Fuzziness and Soft Computing,1434-9922 ;3703-030-00237-3 Includes bibliographical references.Introduction -- Problem Description and Related Work -- Concept -- Fuzzy Rulebase Systems -- Parameters and most Possible Ranges -- Rulebase Construction -- Constrained Defuzzification -- Data Comparison -- Experiments -- Conclusion.This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data. It introduces the necessary concepts from spatial data processing and fuzzy rulebase systems and describes the issues experienced when using current regridding algorithms. The main focus of the book is on describing the different modifications needed to make the problem compatible with fuzzy rulebases. It offers a number of examples of out-of-the box thinking to handle aspects such as rulebase construction, defuzzification, spatial data comparison, etc. At first, the emphasis is put on the newly developed method, and additional datasets containing information on the underlying spatial distribution of the data are identified. After this, an artificial intelligent system (in the form of a fuzzy inference system) is constructed using this knowledge and then applied on the input data to perform the regridding. The book offers an example of how an apparently simple problem can pose many different challenges, even when trying to solve it with existing soft computing technologies. The workflow and solutions to solve these challenges are universal and may therefore be broadly applied into other contexts.Studies in Fuzziness and Soft Computing,1434-9922 ;370Computational intelligenceData miningArtificial intelligenceGeographic information systemsComputational Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/T11014Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Geographical Information Systems/Cartographyhttps://scigraph.springernature.com/ontologies/product-market-codes/J13000Computational intelligence.Data mining.Artificial intelligence.Geographic information systems.Computational Intelligence.Data Mining and Knowledge Discovery.Artificial Intelligence.Geographical Information Systems/Cartography.005.74006.312Verstraete Jörgauthttp://id.loc.gov/vocabulary/relators/aut1225058MiAaPQMiAaPQMiAaPQBOOK9910484186203321Artificial Intelligent Methods for Handling Spatial Data2844487UNINA