000			05210nam a22005535i 4500
001			978-3-540-49774-5
003			DE-He213
005			20161121231201.0
007			cr nn 008mamaa
008			100715s2007 gw | s |||| 0|eng d
020			_a9783540497745 _9978-3-540-49774-5
024	7		_a10.1007/978-3-540-49774-5 _2doi
050		4	_aTA329-348
050		4	_aTA640-643
072		7	_aTBJ _2bicssc
072		7	_aMAT003000 _2bisacsh
082	0	4	_a519 _223
245	1	0	_aEvolutionary Computation in Dynamic and Uncertain Environments _h[electronic resource] / _cedited by Shengxiang Yang, Yew-Soon Ong, Yaochu Jin.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2007.
300			_aXXIII, 605 p. _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 ; _v51
505	0		_aOptimum Tracking in Dynamic Environments -- Explicit Memory Schemes for Evolutionary Algorithms in Dynamic Environments -- Particle Swarm Optimization in Dynamic Environments -- Evolution Strategies in Dynamic Environments -- Orthogonal Dynamic Hill Climbing Algorithm: ODHC -- Genetic Algorithms with Self-Organizing Behaviour in Dynamic Environments -- Learning and Anticipation in Online Dynamic Optimization -- Evolutionary Online Data Mining: An Investigation in a Dynamic Environment -- Adaptive Business Intelligence: Three Case Studies -- Evolutionary Algorithms for Combinatorial Problems in the Uncertain Environment of the Wireless Sensor Networks -- Approximation of Fitness Functions -- Individual-based Management of Meta-models for Evolutionary Optimization with Application to Three-Dimensional Blade Optimization -- Evolutionary Shape Optimization Using Gaussian Processes -- A Study of Techniques to Improve the Efficiency of a Multi-Objective Particle Swarm Optimizer -- An Evolutionary Multi-objective Adaptive Meta-modeling Procedure Using Artificial Neural Networks -- Surrogate Model-Based Optimization Framework: A Case Study in Aerospace Design -- Handling Noisy Fitness Functions -- Hierarchical Evolutionary Algorithms and Noise Compensation via Adaptation -- Evolving Multi Rover Systems in Dynamic and Noisy Environments -- A Memetic Algorithm Using a Trust-Region Derivative-Free Optimization with Quadratic Modelling for Optimization of Expensive and Noisy Black-box Functions -- Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem -- Search for Robust Solutions -- Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty -- Evolving the Tradeoffs between Pareto-Optimality and Robustness in Multi-Objective Evolutionary Algorithms -- Evolutionary Robust Design of Analog Filters Using Genetic Programming -- Robust Salting Route Optimization Using Evolutionary Algorithms -- An Evolutionary Approach For Robust Layout Synthesis of MEMS -- A Hybrid Approach Based on Evolutionary Strategies and Interval Arithmetic to Perform Robust Designs -- An Evolutionary Approach for Assessing the Degree of Robustness of Solutions to Multi-Objective Models -- Deterministic Robust Optimal Design Based on Standard Crowding Genetic Algorithm.
520			_aThis book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering systems is inevitable. Representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums, are presented. "Evolutionary Computation in Dynamic and Uncertain Environments" is a valuable reference for scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, natural computing and evolutionary computation.
650		0	_aEngineering.
650		0	_aArtificial intelligence.
650		0	_aStatistics.
650		0	_aApplied mathematics.
650		0	_aEngineering mathematics.
650		0	_aComputational intelligence.
650	1	4	_aEngineering.
650	2	4	_aAppl.Mathematics/Computational Methods of Engineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
700	1		_aYang, Shengxiang. _eeditor.
700	1		_aOng, Yew-Soon. _eeditor.
700	1		_aJin, Yaochu. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783540497721
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v51
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-540-49774-5
912			_aZDB-2-ENG
950			_aEngineering (Springer-11647)
999			_c509777 _d509777