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020 _a9783030002381
_9
024 7 _a10.1007/978-3-030-00238-1
_2doi
040 _bspa
_dES-MaUEC
050 4 _aQA76.9.D343
_b2019 EB
100 1 _aVerstraete, Jörg.
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aArtificial Intelligent Methods for Handling Spatial Data :
_bFuzzy Rulebase Systems and Gridded Data Problems
_cby Jörg Verstraete.
264 1 _aCham
_bSpringer International Publishing :
_bImprint: Springer
_c2019.
300 _a1 recurso en línea (XVI, 135 páginas)
_b 53 ilustraciones,46 ilustraciones a color
347 _atext file
_bPDF
490 0 _aStudies in Fuzziness and Soft Computing
_x1434-9922 ;
_v370
505 0 _aIntroduction -- Problem Description and Related Work -- Concept -- Fuzzy Rulebase Systems -- Parameters and most Possible Ranges -- Rulebase Construction -- Constrained Defuzzification -- Data Comparison -- Experiments -- Conclusion.
520 3 _aThis 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.
650 7 _aData mining
_2embne
_9162648
710 2 _aSpringerLink (Online service)
_9106996
776 0 8 _iPrinted edition:
_z9783030002374
776 0 8 _iPrinted edition:
_z9783030002398
776 0 8 _iPrinted edition:
_z9783030130954
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-00238-1
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490 0 _aIntelligent Technologies and Robotics (Springer-42732)
942 _2lcc
_cLE
988 _aPrimersemestre_2019_Robotics
998 _aSI
_a_alco
_a_vill
_b10/2019
_cm
_dz
_ea
_feng
_ggw
_h0
999 _c111319
_d111319
_x1