| 書目名稱 | Evolutionary Computation in Dynamic and Uncertain Environments |
| 編輯 | Shengxiang Yang,Yew-Soon Ong,Yaochu Jin |
| 視頻video | http://file.papertrans.cn/318/317893/317893.mp4 |
| 概述 | State of the art of evolutionary algorithms in dynamic and uncertain environments.Includes supplementary material: |
| 叢書名稱 | Studies in Computational Intelligence |
| 圖書封面 |  |
| 描述 | Evolutionary computation is a class of problem optimization methodology with the inspiration from the natural evolution of species. In nature, the population of a species evolves by means of selection and variation. These two principles of natural evolution form the fundamental of evolutionary - gorithms (EAs). During the past several decades, EAs have been extensively studied by the computer science and arti?cial intelligence communities. As a classofstochasticoptimizationtechniques,EAscanoftenoutperformclassical optimization techniques for di?cult real world problems. Due to the ease of use and robustness, EAs have been applied to a wide variety of optimization problems. Most of these optimization problems ta- led are stationary and deterministic. However, many real-world optimization problems are subjected to dynamic and uncertain environments that are often impossible to avoid in practice. For example, the ?tness function is uncertain or noisy as a result of simulation errors, measurement errors or approximation errors. In addition, the design variables or environmental conditions may also perturb or change over time. For these dynamic and uncertain optimization problems, the o |
| 出版日期 | Book 2007 |
| 關(guān)鍵詞 | algorithm; algorithms; artificial intelligence; data mining; evolution; evolutionary algorithm; evolutiona |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-540-49774-5 |
| isbn_softcover | 978-3-642-08065-4 |
| isbn_ebook | 978-3-540-49774-5Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer-Verlag Berlin Heidelberg 2007 |
|Archiver|手機(jī)版|小黑屋|
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