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Titlebook: Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods; Chris Aldrich,Lidia Auret Book 2013 Springer-Verlag Lon

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發(fā)表于 2025-3-21 18:13:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods
編輯Chris Aldrich,Lidia Auret
視頻videohttp://file.papertrans.cn/943/942529/942529.mp4
概述Describes the latest developments in nonlinear methods and their application in fault diagnosis.Discusses in detail several advances in machine learning theory.Contains numerous case studies with real
叢書(shū)名稱Advances in Computer Vision and Pattern Recognition
圖書(shū)封面Titlebook: Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods;  Chris Aldrich,Lidia Auret Book 2013 Springer-Verlag Lon
描述This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.
出版日期Book 2013
關(guān)鍵詞Classification Trees; Fault Detection; Fault Identification; Kernel-based Methods; Neural Networks; Regre
版次1
doihttps://doi.org/10.1007/978-1-4471-5185-2
isbn_softcover978-1-4471-7160-7
isbn_ebook978-1-4471-5185-2Series ISSN 2191-6586 Series E-ISSN 2191-6594
issn_series 2191-6586
copyrightSpringer-Verlag London 2013
The information of publication is updating

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Chris Aldrich,Lidia Aureteory to the teachings of sense, intellect, and philosophical presupposition — that Kepler fashioned his own theory. In short, Kepler’s achievement can be fully appreciated only if viewed within a disciplinary tradition. This will not strike historians as a novel thesis; the novelty will come if we put it into practice.
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2191-6586 y state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.978-1-4471-7160-7978-1-4471-5185-2Series ISSN 2191-6586 Series E-ISSN 2191-6594
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and the abelian Chern-Simons term and whether this generalization leads to novel statistics. This inquiry is of relevance for example for the strongly coupled Hubbard model which has an .(2) gauge invariance. and where it is possible that the effective action of the connection fields contains a Chern-Simons term.
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Chris Aldrich,Lidia Auretfootpoints and propagate along the loops with approximate sound speed (.. ≈ ti 130–190 km s.). These EUV brightenings are possibly related to other dynamic EUV phenomena that have been reported as ‘explosive events’, bi-directional EUV jets, ‘blinkers’, or wave-like disturbances in coronal loops and plumes.
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