Statistical process monitoring using advanced data-driven and deep learning approaches : theory and practical applications /: theory and practical applications. (2020)

• Record Type: Book
• Further Information: Note: Fouzi Harrou, Ying Sun, Amanda S. Hering, Muddu Madakyaru, Abdelkader Dairi.
• Authors: Harrou, Fouzi; Sun, Ying; Hering, Amanda S; Madakyaru, Muddu; Dairi, Abdelkader
• Contents: 1. Introduction 2. Linear Latent Variable Regression (LVR)-Based Process Monitoring 3. Fault attribution 4. Nonlinear latent variable regression methods 5. Multiscale latent variable regression-based process monitoring methods 6. Unsupervised deep learning-based process monitoring methods 7. Unsupervised recurrent deep learning schemes for process monitoring 8. Case studies 9. Conclusions and future perspectives
• Publisher Details: Amsterdam : Elsevier
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 629.895; Process control -- Statistical methods; Multivariate analysis -- Data processing; Machine learning
• Languages: English
• ISBNs: 9780128193662
• Related ISBNs: 9780128193655
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.