LEADER 05384nam 22007575 450 001 9910337471503321 005 20200702205738.0 010 $a3-319-98566-3 024 7 $a10.1007/978-3-319-98566-4 035 $a(CKB)4100000007110892 035 $a(MiAaPQ)EBC5583575 035 $a(DE-He213)978-3-319-98566-4 035 $a(Au-PeEL)EBL5583575 035 $a(CaPaEBR)ebr11636371 035 $a(OCoLC)1061148147 035 $a(PPN)231463588 035 $a(EXLCZ)994100000007110892 100 $a20181031d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNatural Computing for Unsupervised Learning /$fedited by Xiangtao Li, Ka-Chun Wong 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (272 pages) $cillustrations 225 1 $aUnsupervised and Semi-Supervised Learning,$x2522-848X 311 $a3-319-98565-5 327 $aIntroduction -- Part I ? Basic Natural Computing Techniques for Unsupervised Learning -- Hard Clustering using Evolutionary Algorithms -- Soft Clustering using Evolutionary Algorithms -- Fuzzy / Rough Set Systems for Unsupervised Learning -- Unsupervised Feature Selection using Evolutionary Algorithms -- Unsupervised Feature Selection using Artificial Neural Networks -- Part II ? Advanced Natural Computing Techniques for Unsupervised Learning -- Hybrid Genetic Algorithms for Feature Subset Selection in Model-Based Clustering -- Nature-Inspired Optimization Approaches for Unsupervised Feature Selection -- Co-Evolutionary Approaches for Unsupervised Learning -- Mining Evolving Patterns using Natural Computing Techniques -- Multi-objective Optimization for Unsupervised Learning -- Many-objective Optimization for Unsupervised Learning -- Part III ? Applications -- Unsupervised Identification of DNA-binding Proteins using Natural Computing Techniques -- Parallel Solution-based Natural Clustering Techniques on Railway Engineering data -- Natural Computing Techniques for Community Detection on Online Social Networks -- Big Data Challenges and Scalability in Natural Computing for Unsupervised Learning -- Conclusion. 330 $aThis book highlights recent research advances in unsupervised learning using natural computing techniques such as artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, artificial life, quantum computing, DNA computing, and others. The book also includes information on the use of natural computing techniques for unsupervised learning tasks. It features several trending topics, such as big data scalability, wireless network analysis, engineering optimization, social media, and complex network analytics. It shows how these applications have triggered a number of new natural computing techniques to improve the performance of unsupervised learning methods. With this book, the readers can easily capture new advances in this area with systematic understanding of the scope in depth. Readers can rapidly explore new methods and new applications at the junction between natural computing and unsupervised learning. Includes advances on unsupervised learning using natural computing techniques Reports on topics in emerging areas such as evolutionary multi-objective unsupervised learning Features natural computing techniques such as evolutionary multi-objective algorithms and many-objective swarm intelligence algorithms. 410 0$aUnsupervised and Semi-Supervised Learning,$x2522-848X 606 $aElectrical engineering 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aPattern recognition 606 $aArtificial intelligence 606 $aData mining 606 $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aElectrical engineering. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aPattern recognition. 615 0$aArtificial intelligence. 615 0$aData mining. 615 14$aCommunications Engineering, Networks. 615 24$aSignal, Image and Speech Processing. 615 24$aPattern Recognition. 615 24$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 676 $a006.38 702 $aLi$b Xiangtao$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWong$b Ka-Chun$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910337471503321 996 $aNatural Computing for Unsupervised Learning$92256452 997 $aUNINA