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Titlebook: Hybrid Value Creation; Vivek K. Velamuri Book 2013 Springer Fachmedien Wiesbaden 2013

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樓主: Grant
31#
發(fā)表于 2025-3-26 21:06:29 | 只看該作者
Vivek K. Velamuriarm optimization algorithm with an adaptive neighborhood search, and used it to solve traveling salesman problem (TSP). Based on the analysis and optimization of the different genetic operations, a new adaptive DGSO algorithm is presented (ADGSO), which is effective for both local search and global
32#
發(fā)表于 2025-3-27 02:29:16 | 只看該作者
33#
發(fā)表于 2025-3-27 09:10:21 | 只看該作者
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發(fā)表于 2025-3-27 11:44:32 | 只看該作者
35#
發(fā)表于 2025-3-27 13:56:33 | 只看該作者
36#
發(fā)表于 2025-3-27 21:16:17 | 只看該作者
Vivek K. Velamuriicant computational resources and exhibiting lower efficiency. Class incremental learning can be applied to online fault diagnosis, effectively reducing resource consumption. However, the model often experiences catastrophic forgetting during the training process, a problem that can be addressed by
37#
發(fā)表于 2025-3-28 01:34:44 | 只看該作者
Vivek K. Velamurifunctional subsystems. Accurate and efficient anomaly detection for Multivariate Time Series (MTS) with rich temporal and spatial information generated by highly intertwined sensors and actuators in CPS to reduce the negative influence caused by abnormalities. Since existing methods with temporal mo
38#
發(fā)表于 2025-3-28 04:09:45 | 只看該作者
Vivek K. Velamuri one hand, studies on natural swarm intelligence rarely consider how this advantage keeps stable in evolution. On the other hand, evolutionary theories used to neglect the change of absolute fitness at the group level. Nevertheless, social profits are not evenly distributed to individuals. An anti-p
39#
發(fā)表于 2025-3-28 06:50:20 | 只看該作者
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