ONLY $9.90 DELIVERY INFO

Close Notification

Your cart does not contain any items

Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data by Chunhui Zhao (The State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China) at Abbey's Bookshop,
Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data
— —
Chunhui Zhao (The State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China) Wanke Yu, PhD (The State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China)

Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Chunhui Zhao (The State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China),  Wanke Yu, PhD (The State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China)

$363.95

Paperback

Not in-store but you can order this
How long will it take?
English
Academic Press Inc
25 July 2025
Mechanical engineering; Production engineering
Spatio-Temporal Learning Using Irregular Data for Complex Dynamic Processes introduces learning, modeling, and monitoring methods for highly complex dynamic processes with irregular data. Two classes of robust modeling methods are highlighted, including low-rank characteristic of matrices and heavy-tailed characteristic of distributions. In this class, the missing data, ambient noise, and outlier problems are solved using low-rank matrix complement for monitoring model development. Secondly, the Laplace distribution is explored, which is adopted to measure the process uncertainty to develop robust monitoring models.

The book not only discusses the complex models but also their real-world applications in industry.
By:   , , , , , ,
Imprint:   Academic Press Inc
Country of Publication:   United States [Currently unable to ship to USA: see Shipping Info]
Dimensions:   Height: 229mm,  Width: 152mm, 
Weight:   450g
ISBN:   9780443336751
ISBN 10:   044333675X
Pages:   258
Publication Date:  
Audience:   Professional and scholarly ,  College/higher education ,  Undergraduate ,  Further / Higher Education
Format:   Paperback
Publisher's Status:   Active
1. Introduction 2. Low-Rank Characteristic and Temporal Correlation Analytics for Incipient Industrial Fault Detection with Missing Data 3. A Robust Dissimilarity Distribution Analytics with Laplace Distribution for Incipient Industrial Fault Detection 4. Variational Bayesian Student’s-t Mixture Model with Closed-Form Missing Value Imputation for Robust Process Monitoring of Low-Quality Data 5. Stationary Subspace Analysis based Hierarchical Model for Batch Processes Monitoring 6. Recursive Cointegration Analytics for Adaptive Monitoring of Nonstationary Industrial Processes with both Static and Dynamic Variations 7. Incremental Variational Bayesian Gaussian Mixture Model with Decremental Optimization for Distribution Accommodation and Fine-Scale Adaptive Process Monitoring 8. MoniNet with Concurrent Analytics of Temporal and Spatial Information for Fault Detection in Industrial Processes 9. Meticulous Process Monitoring with Multiscale Convolutional Feature Extraction

Chunhui Zhao is a Qiushi distinguished professor at Zhejiang University in China, and an expert in intelligent industrial monitoring with 20 years of experience in this field. She has authored or co-authored more than 400 papers in peer-reviewed international journals and conferences. Her research interests include statistical machine learning and data mining for industrial applications. Wanke Yu is a research fellow at the School of Electrical & Electronic Engineering, Nanyang Technological University in Singapore. Wanke Yu received his Ph.D. degree in automatic control from Zhejiang University, Hangzhou, China, in 2020. His research interests include probabilistic graphic model, deep neural network, and nonconvex optimization, and their applications to process control.

See Also

Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Design of Functional Polymer Nanocomposites...

Interface and Interphase Reactions,...

Rotimi Sadiku (Tshwane University...

Paperback

$454.95 

Not in-store but you can order this

ADD +
Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Risk, Reliability and Resilience...

Sachin Mangla (Professor, OP Jindal...

Paperback

$382.95 

Not in-store but you can order this

ADD +
Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Lehrbuch der Mechanik. Zweiter Band...

Martin Ohm

Paperback

$64.95  $55.02

Not in-store but you can order this

ADD +
Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Optoelectronics and Spintronics...

James Ayodele Oke

Paperback

$135.95  $108.86

Not in-store but you can order this

ADD +
Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Heat Treatment of Soft and Medium...

Federico Giolitti

Paperback

$55.95  $47.68

Not in-store but you can order this

ADD +
Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data

Additive Manufacturing of Magnetic...

Techniques, Materials, Applications,...

Moataz Attallah, Professor of Advanced...

Paperback

$522.95 

Not in-store but you can order this

ADD +