LEADER 03749nam 22006855 450 001 9910437926103321 005 20251113185824.0 010 $a9781283912501 010 $a1283912503 010 $a9783642330421 010 $a3642330428 024 7 $a10.1007/978-3-642-33042-1 035 $a(CKB)2670000000253933 035 $a(EBL)1082640 035 $a(OCoLC)811249949 035 $a(SSID)ssj0000767205 035 $a(PQKBManifestationID)11451751 035 $a(PQKBTitleCode)TC0000767205 035 $a(PQKBWorkID)10739893 035 $a(PQKB)10373021 035 $a(DE-He213)978-3-642-33042-1 035 $a(MiAaPQ)EBC1082640 035 $a(PPN)168323397 035 $a(EXLCZ)992670000000253933 100 $a20120913d2013 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSynergies of Soft Computing and Statistics for Intelligent Data Analysis /$fedited by Rudolf Kruse, Michael R. Berthold, Christian Moewes, María Ángeles Gil, Przemys?aw Grzegorzewski, Olgierd Hryniewicz 205 $a1st ed. 2013. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013. 215 $a1 online resource (554 p.) 225 1 $aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v190 300 $aDescription based upon print version of record. 311 08$a9783642330414 311 08$a364233041X 320 $aIncludes bibliographical references and index. 327 $aPART I Invited Papers -- PART II Foundations -- PART III Statistical Methods -- PART IV Mathematical Aspects -- PART V Engineering. 330 $aIn recent years there has been a growing interest to extend classical methods for data analysis. The aim is to allow a more flexible modeling of phenomena such as uncertainty, imprecision or ignorance. Such extensions of classical probability theory and statistics are useful in many real-life situations, since uncertainties in data are not only present in the form of randomness --- various types of incomplete or subjective information have to be handled. About twelve years ago the idea of strengthening the dialogue between the various research communities in the field of data analysis was born and resulted in the International Conference Series on Soft Methods in Probability and Statistics (SMPS). This book gathers contributions presented at the SMPS'2012 held in Konstanz, Germany. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems. 410 0$aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v190 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a519.5 701 $aKruse$b Rudolf$0102093 712 12$aInternational Conference on Soft Methods in Probability and Statistics$d(6th :$f2012 :$eKonstanz, Germany) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437926103321 996 $aSynergies of soft computing and statistics for intelligent data analysis$94184387 997 $aUNINA