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Titlebook: Artificial Intelligence for Smart Manufacturing; Methods, Application Kim Phuc Tran Book 2023 The Editor(s) (if applicable) and The Author(

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樓主: Embolism
11#
發(fā)表于 2025-3-23 10:35:22 | 只看該作者
1614-7839 lications based on AI techniques.Helps readers and practitio.This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry
12#
發(fā)表于 2025-3-23 15:32:16 | 只看該作者
Approaches to Help in Organizations,tional solutions, which are often non-industrialized, with a new data-based method learned from the simulation of the plant behaviors and using recurrent neural networks (RNN) with short-term and long-term memory (Long short-term memory, LSTM).
13#
發(fā)表于 2025-3-23 18:38:55 | 只看該作者
14#
發(fā)表于 2025-3-24 01:59:33 | 只看該作者
https://doi.org/10.1007/978-3-322-93671-4ate the operating status of the papermaking process. The verification results showed that the proposed model has a fault prediction accuracy of 76.8% and a recall rate of 72.5%, which allows anomalous data to be observed in advance, providing valuable time for subsequent fault diagnosis.
15#
發(fā)表于 2025-3-24 06:26:15 | 只看該作者
16#
發(fā)表于 2025-3-24 10:30:24 | 只看該作者
17#
發(fā)表于 2025-3-24 13:20:27 | 只看該作者
18#
發(fā)表于 2025-3-24 16:36:14 | 只看該作者
19#
發(fā)表于 2025-3-24 21:57:05 | 只看該作者
Multi-objective Optimization of Flexible Flow-Shop Intelligent Scheduling Based on a Hybrid Intelli optimize the established two-stage intelligent scheduling model. Finally, a papermaking production process is taken as an example to comprehensively evaluate the performance of the model and the hybrid intelligent algorithm. The experimental results show that the model and algorithm can effectively solve the presented problem.
20#
發(fā)表于 2025-3-25 02:59:50 | 只看該作者
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