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Titlebook: Adaptive and Natural Computing Algorithms; 10th International C Andrej Dobnikar,Uro? Lotri?,Branko ?ter Conference proceedings 2011 Springe

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41#
發(fā)表于 2025-3-28 16:19:21 | 只看該作者
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發(fā)表于 2025-3-28 19:15:24 | 只看該作者
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發(fā)表于 2025-3-29 00:42:21 | 只看該作者
44#
發(fā)表于 2025-3-29 05:32:06 | 只看該作者
45#
發(fā)表于 2025-3-29 08:59:05 | 只看該作者
Stephan Zschocke,E.-J. Speckmannware implementation. These features makes it a good choice for different control applications, like the one presented in this paper. The problem is to navigate a mobile robot (e.g a car) from an initial state to a fixed goal state. The approach applied is backpropagation through time (BPTT). Besides
46#
發(fā)表于 2025-3-29 14:53:29 | 只看該作者
47#
發(fā)表于 2025-3-29 18:20:40 | 只看該作者
Stephan Zschocke,E.-J. Speckmannrm of the model the prediction can be described by analytical formulas and the proposed algorithm is numerically efficient. It is shown that thanks to a clever tuning of the controller most of calculations needed to derive the control value can be performed off–line. Thus, the proposed algorithm has
48#
發(fā)表于 2025-3-29 19:49:18 | 只看該作者
49#
發(fā)表于 2025-3-30 01:56:26 | 只看該作者
https://doi.org/10.1007/978-3-031-30324-1atures influence the model and can be used with any type of regression model in a uniform way. We used different types of models and data sets to demonstrate that the method is a useful tool for explaining, comparing, and identifying errors in regression models.
50#
發(fā)表于 2025-3-30 07:37:43 | 只看該作者
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