Titlebook: Computational Intelligence in Expensive Optimization Problems; Yoel Tenne,Chi-Keong Goh Book 2010 Springer-Verlag Berlin Heidelberg 2010 a

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书目名称Computational Intelligence in Expensive Optimization Problems被引频次




书目名称Computational Intelligence in Expensive Optimization Problems被引频次学科排名




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书目名称Computational Intelligence in Expensive Optimization Problems年度引用学科排名




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书目名称Computational Intelligence in Expensive Optimization Problems读者反馈学科排名

歪曲道理

Obverse

,Die Eindämmung der Gewalt im Großraum,ution of computationally expensive optimization problems. Existing methods developed by other researchers or the authors’ group are overviewed and a new enhancement based on fitness inheritance is proposed. Whereas conventional evolutionary algorithms require a great number of calls to the evaluatio

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Politik und globale Machtprojektion, reduce the number of function evaluations effectively. Although the approximation errors between the true function values and the approximation values are not small, the rough model can estimate the order relation of solutions with fair accuracy. By utilizing this nature of the rough model, we have

NIL

Schriften zur Unternehmensentwicklung algorithms used in the field of computer experiments are based on Kriging (Gaussian process regression). Starting with a spatial predictor including a measure of uncertainty, they proceed by iteratively choosing the point maximizing a criterion which is a compromise between predicted performance an

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一加就喷出

https://doi.org/10.1007/978-3-322-90403-4e help of modern statistical techniques to create powerful strategies for expensive optimization. For example, it shows how the regularization of some parameters of the EDAs probabilistic models can yield dramatic improvements in efficiency. In this context a new class, Shrinkage EDAs, based on shri

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