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Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data - by Chunhui Zhao & Wanke Yu (Paperback)
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Highlights
- Spatio-Temporal Learning Using Irregular Data for Complex Dynamic Processes introduces learning, modeling, and monitoring methods for highly complex dynamic processes with irregular data.
- Author(s): Chunhui Zhao & Wanke Yu
- 258 Pages
- Technology, Mechanical
Description
Book Synopsis
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.Dimensions (Overall): 8.9 Inches (H) x 6.0 Inches (W) x .6 Inches (D)
Weight: .8 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 258
Genre: Technology
Sub-Genre: Mechanical
Publisher: Academic Press
Format: Paperback
Author: Chunhui Zhao & Wanke Yu
Language: English
Street Date: July 25, 2025
TCIN: 1007271864
UPC: 9780443336751
Item Number (DPCI): 247-50-9442
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 0.6 inches length x 6 inches width x 8.9 inches height
Estimated ship weight: 0.8 pounds
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