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Titlebook: Artificial Intelligence and Soft Computing; 22nd International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2023

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61#
發(fā)表于 2025-4-1 02:11:07 | 只看該作者
Periphere und zentrale Venenzug?nge effectively reduce the high computational load of the LM algorithm. The detailed application of proposed methods in the process of learning neural networks is explicitly discussed. Experimental results have been obtained for all proposed methods and they confirm a very good performance of them.
62#
發(fā)表于 2025-4-1 09:18:46 | 只看該作者
G. John,K. Kursatz,J. E. Schmidtrast, biological learning seems to value efficient adaptation to a constantly changing world. Here we build on a recently proposed model of neuronal learning that suggests neurons predict their own future activity to optimize their energy balance. That work proposed a neuronal learning rule that use
63#
發(fā)表于 2025-4-1 13:48:04 | 只看該作者
Periphere und zentrale Venenzug?ngeuming, repetitive, and error-prone process. Instead of manually defining all waypoints for a broad range of cables, automation can provide globally optimized and valid paths for accelerated product development. To establish automated electrical routing, an industrial-oriented application is directly
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