Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods
Author:   Chris Aldrich ,  Lidia Auret
Publisher:   Springer London Ltd
Edition:   Softcover reprint of the original 1st ed. 2013
ISBN:  

9781447171607


Pages:   374
Publication Date:   23 August 2016
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods


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Author:   Chris Aldrich ,  Lidia Auret
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   Softcover reprint of the original 1st ed. 2013
Weight:   6.692kg
ISBN:  

9781447171607


ISBN 10:   1447171608
Pages:   374
Publication Date:   23 August 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- Overview of Process Fault Diagnosis.- Artificial Neural Networks.- Statistical Learning Theory and Kernel-Based Methods.- Tree-Based Methods.- Fault Diagnosis in Steady State Process Systems.- Dynamic Process Monitoring.- Process Monitoring Using Multiscale Methods.

Reviews

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 simulation results qualify the work as a reference textbook for graduate studies in machine learning. (C. K. Raju, Computing Reviews, October, 2013)


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 simulation results qualify the work as a reference textbook for graduate studies in machine learning. (C. K. Raju, Computing Reviews, October, 2013)


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