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Titlebook: Artificial Evolution; 10th International C Jin-Kao Hao,Pierrick Legrand,Marc Schoenauer Conference proceedings 2012 Springer-Verlag Berlin

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樓主: Adentitious
31#
發(fā)表于 2025-3-27 00:48:50 | 只看該作者
32#
發(fā)表于 2025-3-27 03:26:21 | 只看該作者
Kahori Shiba-Fukushima,Yuzuru Imaihen the optimizer is stochastic, the indicators considered lead to real-valued random variables following particular probability distributions. Expressions for the expected value of these distributions are derived, and shown to be directly related to the first-order attainment function.
33#
發(fā)表于 2025-3-27 08:29:17 | 只看該作者
High-Performance Liquid Chromatography, have shown that the same modifications substantially improve the performance of particle swarm optimization and ant colony optimization algorithms. Altogether, these results suggest that population growth coupled with local search help obtain high-quality results.
34#
發(fā)表于 2025-3-27 10:45:03 | 只看該作者
35#
發(fā)表于 2025-3-27 16:59:11 | 只看該作者
Assessment of Olfactory Toxicity in Rodentsial Evolution as the local algorithm. The resulting distributed algorithm is evaluated on a set of well known test functions and its effectiveness is compared against that of a classical distributed Differential Evolution.
36#
發(fā)表于 2025-3-27 21:32:56 | 只看該作者
37#
發(fā)表于 2025-3-27 22:36:06 | 只看該作者
38#
發(fā)表于 2025-3-28 02:50:43 | 只看該作者
Conference proceedings 2012 2011. Initially, 33 full papers and 10 post papers were carefully reviewed and selected from 64 submissions. This book presents the 19 best papers selected from these contributions. The papers are organized in topical sections on ant colony optimization; multi-objective optimization; analysis; impl
39#
發(fā)表于 2025-3-28 07:50:46 | 只看該作者
40#
發(fā)表于 2025-3-28 13:14:19 | 只看該作者
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