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020 _a9783319470542
_9978-3-319-47054-2
024 7 _a10.1007/978-3-319-47054-2
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
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082 0 4 _a006.3
_223
245 1 0 _aNature-Inspired Design of Hybrid Intelligent Systems
_h[electronic resource] /
_cedited by Patricia Melin, Oscar Castillo, Janusz Kacprzyk.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXII, 838 p. 390 illus., 258 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v667
505 0 _aType-2 and Intuitionistic Fuzzy Logic: On the Graphical Representation of Intuitionistic Membership Functions for its use in Intuitionistic Fuzzy Inference Systems -- A gravitational search algorithm using type-2 fuzzy logic for parameter adaptation -- General Type-2 Fuzzy edge detection in the preprocessing of a face recognition system -- Interval Type-2 Fuzzy Possibilistic C-Means Optimization using Particle Swarm Optimization -- Optimization of Type-2 and Type-1 Fuzzy Integrator to Ensemble Neural Network with Fuzzy Weights Adjustment -- Choquet integral and Interval Type-2 Fuzzy Choquet integral for edge detection -- An Overview of Granular Computing using Fuzzy Logic Systems.
520 _aThis book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.
650 0 _aComputational intelligence.
_97716
650 1 4 _aComputational Intelligence.
_97716
700 1 _aMelin, Patricia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_960158
700 1 _aCastillo, Oscar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_960159
700 1 _aKacprzyk, Janusz.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_960160
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319470535
776 0 8 _iPrinted edition:
_z9783319470559
776 0 8 _iPrinted edition:
_z9783319836508
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v667
_960162
856 4 0 _uhttps://doi.org/10.1007/978-3-319-47054-2
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80488
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