| 000 | 05380nam a22005895i 4500 | ||
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| 001 | 978-3-642-34859-4 | ||
| 003 | DE-He213 | ||
| 005 | 20140220083330.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 121205s2012 gw | s |||| 0|eng d | ||
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_a9783642348594 _9978-3-642-34859-4 |
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| 024 | 7 |
_a10.1007/978-3-642-34859-4 _2doi |
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| 050 | 4 | _aQA75.5-76.95 | |
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_aUYZG _2bicssc |
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_aCOM037000 _2bisacsh |
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_a004.0151 _223 |
| 100 | 1 |
_aBui, Lam Thu. _eeditor. |
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| 245 | 1 | 0 |
_aSimulated Evolution and Learning _h[electronic resource] : _b9th International Conference, SEAL 2012, Hanoi, Vietnam, December 16-19, 2012. Proceedings / _cedited by Lam Thu Bui, Yew Soon Ong, Nguyen Xuan Hoai, Hisao Ishibuchi, Ponnuthurai Nagaratnam Suganthan. |
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2012. |
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| 300 |
_aXIV, 512 p. 193 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v7673 |
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| 505 | 0 | _aThe Influence of the Number of Initial Feasible Solutions on the Performance of an Evolutionary Optimization Algorithm -- Concurrent Differential Evolution Based on Generational Model for Multi-core CPUs -- Figure of Merit Based Fitness Functions in Genetic Programming for Edge Detection -- An Evolutionary Algorithm for the Over-constrained Airport Baggage Sorting Station Assignment Problem -- HEMH2: An Improved Hybrid Evolutionary Metaheuristics for 0/1 Multiobjective Knapsack Problems Guided Reproduction in Differential Evolution -- A Study of Breakout Local Search for the Minimum Sum ColoringProblem -- XCS with Adaptive Action Mapping -- DEAL: A Direction-Guided Evolutionary Algorithm -- Using Hybrid Dependency Identification with a Memetic Algorithm for Large Scale Optimization Problems -- Evolution of Intrinsic Motives in Multi-agent Simulations -- A Hybrid Particle Swarm Optimization Approach to Bernoulli Mixture Models -- An Agent-Based Model for Simulation of Traffic Network Status -- Self-Adaptive Particle Swarm Optimization -- Evaporation Mechanisms for Particle Swarm Optimization -- The Performance and Sensitivity of the Parameters Setting on the Best-so-far ABC -- Incremental Spatial Clustering in Data Mining Using Genetic Algorithm and R-Tree -- Personalized Email Recommender System Based on User Actions -- Emergent Self Organizing Maps for Text Cluster Visualization by Incorporating Ontology Based Descriptors -- Online Handwriting Recognition Using Multi Convolution Neural Networks -- Automatic Discovery of Optimisation Search Heuristics for Two Dimensional Strip Packing Using Genetic Programming -- Solving Graph Coloring Problem by Fuzzy Clustering-Based Genetic Algorithm -- Efficient Neuroevolution for a Quadruped Robot -- Learning and Generating Folk Melodies Using MPF-Inspired Hierarchical Self-Organising Maps -- Multi Objective Learning Classifier Systems Based Hyperheuristics for Modularised Fleet Mix Problem -- Where Should We Stop? An Investigation on Early Stopping for GP Learning -- From Subjective to Objective Metrics for Evolutionary Story Narration Using Event Permutations -- Learning Rule for TSK Fuzzy Logic Systems Using Interval Type-2 Fuzzy Subtractive Clustering -- Constrained Layout Optimization in Satellite Cabin Using a Multiagent Genetic Algorithm -- A Multi-Objective Approach for Master’s Thesis Committees Scheduling Using DMEA -- Coupler-Curve Synthesis of a Planar Four-Bar Mechanism Using NSGA-II -- Interactive GA Flock Brush for Non-Photorealistic Rendering -- Generating Diverse Behaviors of Evolutionary Robots with Speciation for Theory of Mind -- Improving Gender Recognition Using Genetic Algorithms. | |
| 520 | _aThis volume constitutes the proceedings of the 9th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Hanoi, Vietnam, in December 2012. The 50 full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on evolutionary algorithms, theoretical developments, swarm intelligence, data mining, learning methodologies, and real-world applications. | ||
| 650 | 0 | _aComputer science. | |
| 650 | 0 | _aComputational complexity. | |
| 650 | 0 | _aData mining. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aComputer simulation. | |
| 650 | 1 | 4 | _aComputer Science. |
| 650 | 2 | 4 | _aComputation by Abstract Devices. |
| 650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
| 650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
| 650 | 2 | 4 | _aSimulation and Modeling. |
| 650 | 2 | 4 | _aDiscrete Mathematics in Computer Science. |
| 650 | 2 | 4 | _aInformation Systems Applications (incl. Internet). |
| 700 | 1 |
_aOng, Yew Soon. _eeditor. |
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| 700 | 1 |
_aHoai, Nguyen Xuan. _eeditor. |
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| 700 | 1 |
_aIshibuchi, Hisao. _eeditor. |
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| 700 | 1 |
_aSuganthan, Ponnuthurai Nagaratnam. _eeditor. |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783642348587 |
| 830 | 0 |
_aLecture Notes in Computer Science, _x0302-9743 ; _v7673 |
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| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-34859-4 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-LNC | ||
| 999 |
_c103805 _d103805 |
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