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

Zhao

 
9780443336751: Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data
Tapa blanda
ISBN 10: 044333675X ISBN 13: 9780443336751
Editorial: Academic Press, 2025

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca de los autores

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Academic Press
Año de publicación
2025
Idioma
Inglés
ISBN 10 
044333675X
ISBN 13 
9780443336751
Encuadernación
Tapa blanda
Número de páginas
258
Contacto del fabricante
Academic Press
https://shop.elsevier.com/

230 PARK AVENUE, SUITE 800
NY
NY
10169
Estados Unidos de America
Persona responsable
Yeepin GmbH
492000000000
sunshine12232@outlook.com

Alleestr.11
Kaiserslautern
Rheinland-Pfalz
67655
Alemania