Success in Evolutionary Computation

Pirmais vāks
Springer Science & Business Media, 2008. gada 29. febr. - 372 lappuses

Darwinian evolutionary theory is one of the most important theories in human history for it has equipped us with a valuable tool to understand the amazing world around us. There can be little surprise, therefore, that Evolutionary Computation (EC), inspired by natural evolution, has been so successful in providing high quality solutions in a large number of domains. EC includes a number of techniques, such as Genetic Algorithms, Genetic Programming, Evolution Strategy and Evolutionary Programming, which have been used in a diverse range of highly successful applications. This book brings together some of these EC applications in fields including electronics, telecommunications, health, bioinformatics, supply chain and other engineering domains, to give the audience, including both EC researchers and practitioners, a glimpse of this exciting rapidly evolving field.

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Atlasītās lappuses

Saturs

The Automated Design of Artificial Neural Networks
19
A Versatile SurrogateAssisted Memetic Algorithm
42
Data Mining and Intelligent MultiAgent Technologies
73
Evolving Trading Rules
95
A Hybrid Genetic Algorithm for the Protein Folding
120
Optimal Management of Agricultural Systems
141
Circuits by
165
Intuitive Visualization and Interactive Analysis of Pareto
188
Privacy Protection with Genetic Algorithms
215
A Revision of Evolutionary Computation Techniques
239
Survivable Network Design with an Evolution Strategy
263
Evolutionary Computations for Design Optimization
284
Evolving Cooperative Agents in Economy Market Using
313
Optimizing Multiplicative General Parameter Finite Impulse
327
Applying Genetic Algorithms to Optimize the Cost
355

Citi izdevumi - Skatīt visu

Success in Evolutionary Computation
Ang Yang,Yin Shan,Lam Thu Bui
Ierobežota priekšskatīšana - 2008
Success in Evolutionary Computation
Ang Yang,Yin Shan,Lam Thu Bui
Priekšskatījums nav pieejams - 2010

Bieži izmantoti vārdi un frāzes

adaptive agent analog circuits analysis application approach architecture benchmark Berlin Heidelberg chromosome circuit clustering CONNECT constraints convergence cost crossover crosstalk data set described differential evolution elite population encoding evolution strategy evolutionary algorithms Evolutionary Computation evolved example expansion tree experiments expert system filter fitness function fitness value function evaluations gene genetic algorithm genetic operators genetic programming global global optimum heuristic hidden improve individual input inventory iteration k-partition layer MDAV method micro-aggregation multi-objective mutation probability network design neural networks nodes objective function optimisation optimization problem optimum options output parameters Pareto Pareto optimal performance plain population popsize portfolio probability distribution Proceedings production rules proposed protein protein folding random randomly reliability represent rule base search space selection shown in Fig signal simulation solutions structure supply chain surrogate model synthesis Table techniques tion tool topology trust-region undefined points vector warehouse

Bibliogrāfiskā informācija

NosaukumsSuccess in Evolutionary Computation
Grāmatas Studies in Computational Intelligence 92. sējums. sējums
AutorsYin Shan
RedaktoriAng Yang, Yin Shan, Lam Thu Bui
Izdevums:ilustrēts
IzdevējsSpringer Science & Business Media, 2008
ISBN354076285X, 9783540762850
Apjoms372 lappuses
  
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