LEADER 01450nam 2200445 450 001 9910547293903321 005 20221001132243.0 010 $a3-030-90854-2 035 $a(MiAaPQ)EBC6891275 035 $a(Au-PeEL)EBL6891275 035 $a(CKB)21250898600041 035 $a(PPN)26083176X 035 $a(EXLCZ)9921250898600041 100 $a20221001d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAsset management for infrastructure systems $eenergy and water /$fGerd Balzer and Christian Schorn 205 $a2nd ed. 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$dİ2022 215 $a1 online resource (465 pages) 311 08$aPrint version: Balzer, Gerd Asset Management for Infrastructure Systems Cham : Springer International Publishing AG,c2022 9783030908539 320 $aIncludes bibliographical references and index. 606 $aPublic utilities$xManagement 606 $aAsset management accounts 615 0$aPublic utilities$xManagement. 615 0$aAsset management accounts. 676 $a333.79 700 $aBalzer$b Gerd$0866287 702 $aSchorn$b Christian 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910547293903321 996 $aAsset Management for Infrastructure Systems$91933363 997 $aUNINA LEADER 03218nam 2200601I 450 001 9910972881503321 005 20190617112505.0 010 $a9781838671730 010 $a1838671730 010 $a9781838671716 010 $a1838671714 035 $a(CKB)4100000008415740 035 $a(MiAaPQ)EBC5787820 035 $a(UtOrBLW)9781838671716 035 $a(Perlego)954084 035 $a(EXLCZ)994100000008415740 100 $a20190617h20192019 uy 0 101 0 $aeng 135 $aurun||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSelf-learning and adaptive algorithms for business applications $ea guide to adaptive neuro-fuzzy systems for fuzzy clustering under uncertainty conditions /$fZhengbing Hu, Yevgeniy V. Bodyanskiy, and Oleksii K. Tyshchenko 205 $aFirst edition. 210 1$aBingley, UK :$cEmerald Publishing,$d2019. 215 $a1 online resource (117 pages) 225 1 $aEmerald points 311 08$a9781838671747 311 08$a1838671749 320 $aIncludes bibliographical references. 327 $aPrelims -- Introduction -- Review of the problem area -- Adaptive methods of fuzzy clustering -- Kohonen maps and their ensembles for fuzzy clustering tasks -- Simulation results and solutions for practical tasks -- Conclusion -- References. 330 $aIn today's data-driven world, more sophisticated algorithms for data processing are in high demand, mainly when the data cannot be handled with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla, Microsoft, and Facebook in their projects and applications.In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear. Including research relevant to those studying cybernetics, applied mathematics, statistics, engineering, and bioinformatics who are working in the areas of machine learning, artificial intelligence, complex system modeling and analysis, neural networks, and optimization, this is an ideal read for anyone interested in learning more about the fascinating new developments in machine learning. 410 0$aEmerald points. 606 $aBusiness$xData processing 606 $aElectronic data processing 606 $aFuzzy systems 606 $aBusiness & Economics$xResearch & Development$2bisacsh 606 $aNeural networks & fuzzy systems$2bicssc 615 0$aBusiness$xData processing. 615 0$aElectronic data processing. 615 0$aFuzzy systems. 615 7$aBusiness & Economics$xResearch & Development. 615 7$aNeural networks & fuzzy systems. 676 $a004 700 $aHu$b Zhengbing$0898601 702 $aBodyanskiy$b Yevgeniy V. 702 $aTyshchenko$b Oleksii 801 0$bUtOrBLW 801 1$bUtOrBLW 906 $aBOOK 912 $a9910972881503321 996 $aSelf-learning and adaptive algorithms for business applications$94354066 997 $aUNINA