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001 978-3-662-53752-7
003 DE-He213
005 20220801221129.0
007 cr nn 008mamaa
008 161130s2017 gw | s |||| 0|eng d
020 _a9783662537527
_9978-3-662-53752-7
024 7 _a10.1007/978-3-662-53752-7
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
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082 0 4 _a006.3
_223
100 1 _aMönks, Uwe.
_eauthor.
_0(orcid)0000-0003-1015-0697
_1https://orcid.org/0000-0003-1015-0697
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_954279
245 1 0 _aInformation Fusion Under Consideration of Conflicting Input Signals
_h[electronic resource] /
_cby Uwe Mönks.
250 _a1st ed. 2017.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer Vieweg,
_c2017.
300 _aXIX, 240 p. 58 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTechnologien für die intelligente Automation, Technologies for Intelligent Automation,
_x2522-8587
505 0 _aIntroduction -- Scientific State of the Art -- Preliminaries -- Multilayer Attribute-based Conflict-reducing Observation -- Evaluation -- Summary.
520 _aThis work proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation) and the µBalTLCS (fuzzified balanced two-layer conflict solving) fusion algorithm to reduce the impact of conflicts on the fusion result. In addition, a sensor defect detection method, which is based on the continuous monitoring of sensor reliabilities, is presented. The performances of the contributions are shown by their evaluation in the scope of both a publicly available data set and a machine condition monitoring application under laboratory conditions. Here, the MACRO system yields the best results compared to state-of-the-art fusion mechanisms. The author Dr.-Ing. Uwe Mönks studied Electrical Engineering and Information Technology at the OWL University of Applied Sciences (Lemgo), Halmstad University (Sweden), and Aalborg University (Denmark). Since 2009 he is employed at the Institute Industrial IT (inIT) as research associate with project leading responsibilities. During this time he completed his doctorate (Dr.-Ing.) in a cooperative graduation with Ruhr-University Bochum. His research interests are in the area of multisensor and information fusion, pattern recognition, and machine learning.
650 0 _aComputational intelligence.
_97716
650 0 _aSignal processing.
_94052
650 0 _aControl engineering.
_931970
650 0 _aRobotics.
_92393
650 0 _aAutomation.
_92392
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aControl, Robotics, Automation.
_931971
650 2 4 _aArtificial Intelligence.
_93407
710 2 _aSpringerLink (Online service)
_954280
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783662537510
776 0 8 _iPrinted edition:
_z9783662537534
830 0 _aTechnologien für die intelligente Automation, Technologies for Intelligent Automation,
_x2522-8587
_954281
856 4 0 _uhttps://doi.org/10.1007/978-3-662-53752-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79324
_d79324