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Titlebook: Genetic Programming; Second European Work Riccardo Poli,Peter Nordin,Terence C. Fogarty Conference proceedings 1999 Springer-Verlag Berlin

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樓主: Monroe
51#
發(fā)表于 2025-3-30 11:36:38 | 只看該作者
52#
發(fā)表于 2025-3-30 14:51:18 | 只看該作者
Grenzfragen des Nerven- und Seelenlebensight settings. Our approach combines evolutionary algorithms and genetic programming techniques and is based on a new network encoding schema where instead of a string like encoding the graph representation of neural nets is used. This way of “encoding” reduces the computational expense and leads to
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發(fā)表于 2025-3-30 18:42:23 | 只看該作者
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發(fā)表于 2025-3-30 20:42:32 | 只看該作者
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發(fā)表于 2025-3-31 03:21:25 | 只看該作者
Genetic Programming978-3-540-48885-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
56#
發(fā)表于 2025-3-31 07:16:48 | 只看該作者
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發(fā)表于 2025-3-31 12:38:12 | 只看該作者
58#
發(fā)表于 2025-3-31 13:42:53 | 只看該作者
Grenzfragen des Nerven- und Seelenlebensight settings. Our approach combines evolutionary algorithms and genetic programming techniques and is based on a new network encoding schema where instead of a string like encoding the graph representation of neural nets is used. This way of “encoding” reduces the computational expense and leads to a greater variety of network topologies.
59#
發(fā)表于 2025-3-31 18:33:38 | 只看該作者
Mutation in Genetic Programming: A Preliminary Studyresent a novel representation of function nodes, designed to allow the search operators to make smaller movements around the solution space. Using this representation, performance on the even-6-parity problem is improved by three orders of magnitude relative to the estimate given for standard GP in [5].
60#
發(fā)表于 2025-3-31 22:02:20 | 只看該作者
Evolution of Ship Detectors for Satellite SAR Imageryspection of the SAR images taken by satellites. The scheme: (1) affords practical evolution times, (2) is structured to discover fast automatic detectors, (3) can produce small detectors that shed light into the nature of the detection. Detectors compare favorably in accuracy to those obtained using a SOM neural network.
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