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001 978-3-540-75396-4
003 DE-He213
005 20161121230544.0
007 cr nn 008mamaa
008 100301s2008 gw | s |||| 0|eng d
020 _a9783540753964
_9978-3-540-75396-4
024 7 _a10.1007/978-3-540-75396-4
_2doi
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aEngineering Evolutionary Intelligent Systems
_h[electronic resource] /
_cedited by Ajith Abraham, Crina Grosan, Witold Pedrycz.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2008.
300 _aXX, 444 p. 191 illus.
_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,
_x1860-949X ;
_v82
505 0 _aEngineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews -- Genetically Optimized Hybrid Fuzzy Neural Networks: Analysis and Design of Rule-based Multi-layer Perceptron Architectures -- Genetically Optimized Self-organizing Neural Networks Based on Polynomial and Fuzzy Polynomial Neurons: Analysis and Design -- Evolution of Inductive Self-organizing Networks -- Recursive Pattern based Hybrid Supervised Training -- Enhancing Recursive Supervised Learning Using Clustering and Combinatorial Optimization (RSL-CC) -- Evolutionary Approaches to Rule Extraction from Neural Networks -- Cluster-wise Design of Takagi and Sugeno Approach of Fuzzy Logic Controller -- Evolutionary Fuzzy Modelling for Drug Resistant HIV-1 Treatment Optimization -- A New Genetic Approach for Neural Network Design -- A Grammatical Genetic Programming Representation for Radial Basis Function Networks -- A Neural-Genetic Technique for Coastal Engineering: Determining Wave-induced Seabed Liquefaction Depth -- On the Design of Large-scale Cellular Mobile Networks Using Multi-population Memetic Algorithms -- A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem -- Particle Swarm Optimization with Mutation for High Dimensional Problems.
520 _aEvolutionary design of intelligent systems is gaining much popularity due to its capabilities in handling several real world problems involving optimization, complexity, noisy and non-stationary environment, imprecision, uncertainty and vagueness. This edited volume 'Engineering Evolutionary Intelligent Systems' deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business or commerce. This volume comprises of 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
650 0 _aComputer science.
650 0 _aArtificial intelligence.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
700 1 _aAbraham, Ajith.
_eeditor.
700 1 _aGrosan, Crina.
_eeditor.
700 1 _aPedrycz, Witold.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540753957
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v82
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-75396-4
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c500507
_d500507