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Titlebook: Artificial Intelligence and Soft Computing; 12th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

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樓主: Objective
51#
發(fā)表于 2025-3-30 10:05:05 | 只看該作者
52#
發(fā)表于 2025-3-30 12:32:55 | 只看該作者
0302-9743 uded in the first volume are organized in the following topical sections: neural networks and their applications; fuzzy systems and their applications; pattern classification; and computer vision, image and speech analysis.978-3-642-38657-2978-3-642-38658-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
53#
發(fā)表于 2025-3-30 20:18:17 | 只看該作者
https://doi.org/10.1007/978-3-642-38658-9bio-inspired techniques; genetic algorithms; interacting agents; particle swarm optimization; visualizat
54#
發(fā)表于 2025-3-30 23:21:29 | 只看該作者
55#
發(fā)表于 2025-3-31 01:49:40 | 只看該作者
Artificial Intelligence and Soft Computing978-3-642-38658-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
56#
發(fā)表于 2025-3-31 07:08:29 | 只看該作者
57#
發(fā)表于 2025-3-31 12:30:35 | 只看該作者
Massenanwendung von Kleinstprozessrechnernf the Unscented Kalman Filter to the training of the designed neural model is also shown. The final part of this work provides an illustrative example of the application of the proposed methodology to the identification and robust fault detection of the tunnel furnace.
58#
發(fā)表于 2025-3-31 13:45:25 | 只看該作者
Gemma Rius,Xavier Borrisé,Narcís Mestrestra (set of eigenvalues of the graph adjacency matrix) of both networks turn out to obey similar decay rate and characteristic power-law scaling in their middle parts. This extends the set of statistics, which are already confirmed to be similar for both neural models and medical data, by the graph spectrum.
59#
發(fā)表于 2025-3-31 20:09:13 | 只看該作者
60#
發(fā)表于 2025-3-31 23:57:29 | 只看該作者
Designing of State-Space Neural Model and Its Application to Robust Fault Detectionf the Unscented Kalman Filter to the training of the designed neural model is also shown. The final part of this work provides an illustrative example of the application of the proposed methodology to the identification and robust fault detection of the tunnel furnace.
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