Titlebook: Hybrid Evolutionary Algorithms; Ajith Abraham,Crina Grosan,Hisao Ishibuchi Book 2007 Springer-Verlag Berlin Heidelberg 2007 Evolution.Evol

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Hybrid Genetic: Particle Swarm Optimization Algorithm,od. The performance of the hybrid algorithm is illustrated using four test functions. Proportional integral derivative (PID) controllers have been widely used in industrial systems such as chemical process, biomedical process, and in the main steam temperature control system of the thermal power pla

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天真

Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction,mely complex to solve and computationally very intensive. . techniques have assumed considerable importance in attempting to overcome these challenges and so this chapter explores some of these PFP issues. By using the well-known .–. (HP) model, the performance of a number of contemporary nondetermi

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Robust Parametric Image Registration,(possible with noise) to a target image. Hybridization occurs when genetic algorithms are able to determine rough areas of the parameter optimization space, but fail to produce fine tunings for those parameters. In that case, the Newton–Levenberg–Marquardt method is used to refine results. Another i

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https://doi.org/10.1007/978-3-540-73297-6Evolution; Evolutionary Intelligent Systems; Hybrid Evolutionary Algorithms; algorithm; algorithms; archi