Titlebook: Machine Learning for Cyber Physical Systems; Selected papers from Jürgen Beyerer,Christian Kühnert,Oliver Niggemann Conference proceedings‘

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書目名稱Machine Learning for Cyber Physical Systems影響因子(影響力)




書目名稱Machine Learning for Cyber Physical Systems影響因子(影響力)學(xué)科排名




書目名稱Machine Learning for Cyber Physical Systems網(wǎng)絡(luò)公開度




書目名稱Machine Learning for Cyber Physical Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Machine Learning for Cyber Physical Systems被引頻次




書目名稱Machine Learning for Cyber Physical Systems被引頻次學(xué)科排名




書目名稱Machine Learning for Cyber Physical Systems年度引用




書目名稱Machine Learning for Cyber Physical Systems年度引用學(xué)科排名




書目名稱Machine Learning for Cyber Physical Systems讀者反饋




書目名稱Machine Learning for Cyber Physical Systems讀者反饋學(xué)科排名

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地名詞典

Machine Learning for Cyber Physical Systems978-3-662-58485-9Series ISSN 2522-8579 Series E-ISSN 2522-8587

忙碌

https://doi.org/10.1007/978-3-662-58485-9Machine Learning; Artificial Intelligence; Cognitive Robotics; Internet of Things; Computational intelli

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Machine Learning for Enhanced Waste Quantity Reduction: Insights from the MONSOON Industry 4.0 Proje to be optimized via data-driven methodology. We show how the particular problem of waste quantity reduction can be enhanced by means of machine learning. The results presented in this paper are useful for researchers and practitioners in the field of machine learning for cyber-physical systems in data-intensive Industry 4.0 domains.

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Conference proceedings‘‘‘‘‘‘‘‘ 2019ed papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018.?.Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn

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