[PDF.38oe] Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods (Advances in Computer Vision and Pattern Recognition)

Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods (Advances in Computer Vision and Pattern Recognition)

[PDF.xp11] Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods (Advances in Computer Vision and Pattern Recognition)

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 | #3453001 in Books |  Chris Aldrich |  2013-06-16 | Original language:English | PDF # 1 |  9.21 x.88 x6.14l,.0 | File type: PDF | 374 pages

 | Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

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|| ||From the reviews:|“The text elaborates a range of classifiers used for supervised and unsupervised machine learning methods, for different types of processes. … The rich examples of various industrial processes and the illustration of subsequent

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 ex...

You easily download any file type for your gadget.Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods (Advances in Computer Vision and Pattern Recognition)   |  Chris Aldrich, Lidia Auret. A good, fresh read, highly recommended.

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