000 06166cam a2200877 i 4500
001 on1104209023
003 OCoLC
005 20220712091232.0
006 m o d
007 cr cnu|||unuuu
008 190611s2019 enk ob 000 0 eng d
040 _aN$T
_beng
_erda
_epn
_cN$T
_dN$T
_dEBLCP
_dOCLCF
_dUKMGB
_dUKAHL
_dOTZ
_dOCLCQ
_dSFB
_dOCLCQ
_dK6U
_dOCLCO
_dOCLCQ
_dOCLCO
015 _aGBB964754
_2bnb
016 7 _a019349566
_2Uk
020 _a9781838671716
_q(electronic bk.)
020 _a1838671714
_q(electronic bk.)
020 _a9781838671730
_q(ePub ebook)
020 _a1838671730
020 _z9781838671747
029 1 _aAU@
_b000067268534
029 1 _aCHNEW
_b001059161
029 1 _aCHVBK
_b569757649
029 1 _aUKMGB
_b019349566
035 _a(OCoLC)1104209023
037 _a9781838671730
_bEmerald Publishing
050 4 _aHD30.2
072 7 _aBUS
_x082000
_2bisacsh
072 7 _aBUS
_x041000
_2bisacsh
072 7 _aBUS
_x042000
_2bisacsh
072 7 _aBUS
_x085000
_2bisacsh
080 _a658
082 0 4 _a658.4038
_223
049 _aMAIN
100 1 _aHu, Zhengbing,
_eauthor.
_9832282
245 1 0 _aSelf-learning and adaptive algorithms for business applications :
_ba guide to adaptive neuro-fuzzy systems for fuzzy clustering under uncertainty conditions /
_cby Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko.
250 _aFirst edition.
264 1 _aBingley, UK :
_bEmerald Publishing,
_c2019.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aEmerald points
504 _aIncludes bibliographical references.
588 _aOnline resource; title from PDF title page (EBSCO, viewed June 13, 2019).
505 0 _aFront Cover; Self-Learning and Adaptive Algorithms for Business Applications; Copyright Page; Contents; Acknowledgment; Introduction; Chapter 1 Review of the Problem Area; 1.1. Learning and Self-learning Procedures; 1.2. Clustering; 1.2.1. Clustering Methods; 1.3. Fuzzy Sets and Fuzzy Logic; 1.3.1. Fuzzy Inference Systems and Fuzzy Control; 1.3.2. Type-2 Fuzzy Logic; 1.3.2.1. Interval Type-2 Fuzzy Sets; 1.3.2.2. Model Reduction; 1.3.2.3. Type-2 Fuzzy Clustering; 1.4. Neural Networks and Their Learning Methods; 1.4.1. Artificial Neural Networks; 1.4.2. Neural Networks' Learning
505 8 _a1.4.3. Recurrent Neural Networks1.5. Neuro-fuzzy Systems; Chapter 2 Adaptive Methods of Fuzzy Clustering; 2.1. An Objective Function for Fuzzy Clustering; 2.2. Optimization of the Objective Function; 2.3. A Linear Variable Fuzzifier; 2.3.1. Adaptive Fuzzy Clustering with a Variable Fuzzifier; 2.3.2. Possibilistic Fuzzy Clustering with a Variable Fuzzifier; 2.3.3. A Suppression Procedure for Fuzzy Clustering; 2.4. Methods Based on the Gustafson-Kessel Procedure; 2.4.1. The Basic Gustafson-Kessel Method; 2.4.2. A Possibilistic Version of the Gustafson-Kessel Method
505 8 _a2.4.3. Adaptive Versions of the Gustafson-Kessel Algorithm2.5. A Robust Fuzzy Clustering Method Based on the Cauchy Criterion; 2.5.1. The Probabilistic Approach; 2.5.2. The Possibilistic Approach; Chapter 3 Kohonen Maps and Their Ensembles for Fuzzy Clustering Tasks; 3.1. The Competitive Learning; 3.2. Kohonen Neural Networks; 3.3. Modifications of Kohonen Self-organizing Maps; 3.4. Ensembles and Their Learning Methods; 3.4.1. Reasons for Using Ensembles; 3.4.2. Basic Notions of the Theory of Collective Output Systems; 3.4.2.1. Confidence; 3.4.2.2. Diversification
505 8 _a3.4.2.3. Incremental Ensembles' Learning3.4.3. Methods for Building Ensembles; 3.4.3.1. An Algebraic Combination; 3.4.3.2. A Weighted Combination; 3.4.3.3. Complex Systems of the Collective Output; 3.5. Ensembles of Neuro-fuzzy Kohonen Networks; 3.6. Fuzzy Type-2 Clustering Using Ensembles of Modified Neuro-fuzzy Kohonen Networks; Chapter 4 Simulation Results and Solutions for Practical Tasks; 4.1. Simulation of the Adaptive Neuro-fuzzy Kohonen Network with a Variable Fuzzifier; 4.1.1. Comparative Efficiency; 4.1.2. The Fuzzifier's Influence; 4.1.3. Influence of the Suppression Parameter
505 8 _a4.2. Simulation of Adaptive Versions the Gustafson-Kessel Algorithm4.3. Simulation of the Robust Clustering Method Based on the Cauchy Criterion; 4.4. Solving the Task of Automated Cataloging of Illustrative Materials; Conclusion; References
520 _aIn 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.
590 _aeBooks on EBSCOhost
_bEBSCO eBook Subscription Academic Collection - Worldwide
650 0 _aElectronic data processing.
_942124
650 0 _aBusiness
_xData processing.
650 0 _aFuzzy systems.
650 6 _aGestion
_xInformatique.
_9951042
650 6 _aSystèmes flous.
_9905335
650 7 _aNeural networks & fuzzy systems.
_2bicssc
_9855107
650 7 _aBUSINESS & ECONOMICS
_xIndustrial Management.
_2bisacsh
_991996
650 7 _aBUSINESS & ECONOMICS
_xManagement.
_2bisacsh
_991997
650 7 _aBUSINESS & ECONOMICS
_xManagement Science.
_2bisacsh
_991998
650 7 _aBUSINESS & ECONOMICS
_xOrganizational Behavior.
_2bisacsh
_991999
650 7 _aBusiness
_xData processing.
_2fast
_0(OCoLC)fst00842293
650 7 _aElectronic data processing.
_2fast
_0(OCoLC)fst00906956
_942124
650 7 _aFuzzy systems.
_2fast
_0(OCoLC)fst00936814
655 4 _aElectronic books.
700 1 _aBodyanskiy, Yevgeniy V.,
_eauthor
_9832283
700 1 _aTyshchenko, Oleksii,
_eauthor.
_9832284
776 0 8 _iPrint version :
_z9781838671747
830 0 _aEmerald points.
856 4 0 _uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2040570
938 _aAskews and Holts Library Services
_bASKH
_nAH35976434
938 _aAskews and Holts Library Services
_bASKH
_nBDZ0039757353
938 _aProQuest Ebook Central
_bEBLB
_nEBL5787820
938 _aEBSCOhost
_bEBSC
_n2040570
994 _a92
_bINOPJ
999 _c2839498
_d2839498