Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

Algorithms for intelligent fault diagnosis of automated operations offer significant benefits to the manufacturing and process industries. Furthermore, machine learning methods enable such monitoring systems to handle nonlinearities and large volumes of data. This unique text/reference describes in...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς:	Aldrich, Chris (Συγγραφέας), Auret, Lidia (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή:	SpringerLink (Online service)
Μορφή:	Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:	English
Έκδοση:	London : Springer London : Imprint: Springer, 2013.
Σειρά:	Advances in Computer Vision and Pattern Recognition,
Θέματα:	Computer science. Artificial intelligence. Computer Science. Artificial Intelligence (incl. Robotics).
Διαθέσιμο Online:	Full Text via HEAL-Link

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