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Titlebook: Computational Intelligence Paradigms; Innovative Applicati Lakhmi C. Jain,Mika Sato-Ilic,Canicious Abeynayake Book 2008 Springer-Verlag Ber

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發(fā)表于 2025-3-23 10:35:24 | 只看該作者
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發(fā)表于 2025-3-23 16:17:39 | 只看該作者
https://doi.org/10.1007/978-981-15-4650-1should be similar to each other) with constraints on the number of data per cluster. The proposed techniques can be used for various purposes. If a set of items, jobs or customers has to be distributed among a limited number of resources and the workload for each resource shall be balanced, clusters
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發(fā)表于 2025-3-24 06:36:40 | 只看該作者
https://doi.org/10.1057/9780312299156rtant to encode linked variables tightly for simple GAs, it is sometimes difficult because it requires enough knowledge of problems to be solved. In order to solve real-world problems effectively even if the knowledge is not available, we need to analyze gene linkage..We review algorithms which have
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發(fā)表于 2025-3-24 11:57:43 | 只看該作者
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Thinking About Urban Materialityl concept of this new, innovative computing field. The main constituents of CI, which include artificial neural networks, fuzzy systems, and evolutionary algorithms, are explained. In addition, different hybrid CI models arisen from synergy of neural, fuzzy, and evolutionary computational paradigms are discussed.
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