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Titlebook: Applications of Evolutionary Computing; EvoWorkshops 2004: E Günther R. Raidl,Stefano Cagnoni,Giovanni Squiller Conference proceedings 2004

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41#
發(fā)表于 2025-3-28 17:56:31 | 只看該作者
Applications of Evolutionary Computing978-3-540-24653-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
42#
發(fā)表于 2025-3-28 21:26:47 | 只看該作者
Encyclopedia of Immunotoxicologys describing in detail how the algorithm works, we report experimental results that justify important implementation choices, such as the introduction of speciation mechanisms and the extensive application of local search. Test runs on 48-mer chains show that the proposed algorithm has promising search capabilities.
43#
發(fā)表于 2025-3-28 23:09:29 | 只看該作者
44#
發(fā)表于 2025-3-29 04:08:27 | 只看該作者
Günther R. Raidl,Stefano Cagnoni,Giovanni SquillerIncludes supplementary material:
45#
發(fā)表于 2025-3-29 09:46:44 | 只看該作者
46#
發(fā)表于 2025-3-29 14:01:12 | 只看該作者
47#
發(fā)表于 2025-3-29 16:54:36 | 只看該作者
48#
發(fā)表于 2025-3-29 20:28:33 | 只看該作者
https://doi.org/10.1007/978-3-642-54596-2se statistical techniques to preprocess the labeled datasets, these methods are generally not linked with the combinatorial properties of the final solutions. We prove that it is .-hard to obtain an appropriate set of thresholds that will transform a given dataset into a binary instance of a robust
49#
發(fā)表于 2025-3-30 01:39:41 | 只看該作者
Acute Graft-Versus-Host Diseases in the laboratory. For example, patterns representing nuclear localisation signals (NLSs) are used to predict nuclear localisation. NLSs are not yet well understood, and so the set of currently known NLSs may be incomplete. Here we use genetic programming (GP) to generate RE-based classifiers for
50#
發(fā)表于 2025-3-30 06:23:28 | 只看該作者
Geoff Daniels,Marcela Contrerasa quadratic support vector machine (SVM) are applied to the data for distinguishing between cancer and benign status. On the ovarian dataset SVM gives excellent results, while the prostate dataset seems to be a harder classification problem for SVM. The prostate dataset is futher analyzed by means o
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