LEADER 04460nam 22006975 450 001 9910299739703321 005 20220329215115.0 010 $a3-319-08611-1 024 7 $a10.1007/978-3-319-08611-8 035 $a(CKB)3710000000205408 035 $a(EBL)1783127 035 $a(OCoLC)889264182 035 $a(SSID)ssj0001295659 035 $a(PQKBManifestationID)11682807 035 $a(PQKBTitleCode)TC0001295659 035 $a(PQKBWorkID)11343892 035 $a(PQKB)10247945 035 $a(MiAaPQ)EBC1783127 035 $a(DE-He213)978-3-319-08611-8 035 $a(PPN)17992382X 035 $a(EXLCZ)993710000000205408 100 $a20140722d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRandom sets and random fuzzy sets as ill-perceived random variables $ean introduction for Ph.D. students and practitioners /$fby Inés Couso, Didier Dubois, Luciano Sánchez 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (104 p.) 225 1 $aSpringerBriefs in Computational Intelligence,$x2625-3704 300 $aDescription based upon print version of record. 311 $a3-319-08610-3 320 $aIncludes bibliographical references at the end of each chapters. 327 $aIntroduction -- Random sets as ill-perceived random variables -- Random fuzzy sets as ill-perceived random variables. 330 $aThis short book provides a unified view of the history and theory of random sets and fuzzy random variables, with special emphasis on its use for representing higher-order non-statistical uncertainty about statistical experiments. The authors lay bare the existence of two streams of works using the same mathematical ground, but differing form their use of sets, according to whether they represent objects of interest naturally taking the form of sets, or imprecise knowledge about such objects. Random (fuzzy) sets can be used in many fields ranging from mathematical morphology, economics, artificial intelligence, information processing and statistics per se, especially in areas where the outcomes of random experiments cannot be observed with full precision. This book also emphasizes the link between random sets and fuzzy sets with some techniques related to the theory of imprecise probabilities. This small book is intended for graduate and doctoral students in mathematics or engineering, but also provides an introduction for other researchers interested in this area. It is written from a theoretical perspective. However, rather than offering a comprehensive formal view of random (fuzzy) sets in this context, it aims to provide a discussion of the meaning of the proposed formal constructions based on many concrete examples and exercises. This book should enable the reader to understand the usefulness of representing and reasoning with incomplete information in statistical tasks.  Each chapter ends with a list of exercises. 410 0$aSpringerBriefs in Computational Intelligence,$x2625-3704 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aStatistics  606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17020 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aStatistics . 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 676 $a519.2 700 $aCouso$b Inés$4aut$4http://id.loc.gov/vocabulary/relators/aut$0957743 702 $aDubois$b Didier$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSánchez$b Luciano$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299739703321 996 $aRandom Sets and Random Fuzzy Sets as Ill-Perceived Random Variables$92169645 997 $aUNINA