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100   $a20191226d2019      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aPossibility Theory for the Design of Information Fusion Systems /$fby Basel Solaiman, Éloi Bossé
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (294 pages)
225 1 $aInformation Fusion and Data Science,$x2510-1528
311   $a3-030-32852-X 
327   $aChapter1: Introduction to possibility theory -- Chapter2: Fundamental possibilistic concepts -- Chapter3: Joint Possibility Distributions and Conditioning -- Chapter4: Possibilistic Similarity Measures -- Chapter5: The interrelated uncertainty modeling theories -- Chapter6: Possibility integral -- Chapter7: Fusion operators and decision-making criteria in the framework of possibility theory -- Chapter8: Possibilistic concepts applied to soft pattern classification -- Chapter9: The use of possibility theory in the design of information fusion systems.
330   $aThis practical guidebook describes the basic concepts, the mathematical developments, and the engineering methodologies for exploiting possibility theory for the computer-based design of an information fusion system where the goal is decision support for industries in smart ICT (information and communications technologies). This exploitation of possibility theory improves upon probability theory, complements Dempster-Shafer theory, and fills an important gap in this era of Big Data and Internet of Things. The book discusses fundamental possibilistic concepts: distribution, necessity measure, possibility measure, joint distribution, conditioning, distances, similarity measures, possibilistic decisions, fuzzy sets, fuzzy measures and integrals, and finally, the interrelated theories of uncertainty..uncertainty. These topics form an essential tour of the mathematical tools needed for the latter chapters of the book. These chapters present applications related to decision-making and pattern recognition schemes, and finally, a concluding chapter on the use of possibility theory in the overall challenging design of an information fusion system. This book will appeal to researchers and professionals in the field of information fusion and analytics, information and knowledge processing, smart ICT, and decision support systems.
410  0$aInformation Fusion and Data Science,$x2510-1528
606   $aProbabilities
606   $aStatistics
606   $aMathematical statistics
606   $aSociophysics
606   $aEconophysics
606   $aElectrical engineering
606   $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004
606   $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020
606   $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036
606   $aData-driven Science, Modeling and Theory Building$3https://scigraph.springernature.com/ontologies/product-market-codes/P33030
606   $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035
615  0$aProbabilities.
615  0$aStatistics.
615  0$aMathematical statistics.
615  0$aSociophysics.
615  0$aEconophysics.
615  0$aElectrical engineering.
615 14$aProbability Theory and Stochastic Processes.
615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
615 24$aProbability and Statistics in Computer Science.
615 24$aData-driven Science, Modeling and Theory Building.
615 24$aCommunications Engineering, Networks.
676   $a511.322
700   $aSolaiman$b Basel$4aut$4http://id.loc.gov/vocabulary/relators/aut$0781688
702   $aBossé$b Éloi$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910739416203321
996   $aPossibility Theory for the Design of Information Fusion Systems$93552896
997   $aUNINA