True sparse PCA for reducing the number of essential sensors in virtual metrology-Reference-Cited by-同舟云学术

True sparse PCA for reducing the number of essential sensors in virtual metrology

Published:2023-05-28 Issue: Volume: Page:1-16
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Xie Yifan¹,Wang Tianhui¹,Jeong Young-Seon²,Tosyali Ali³,Jeong Myong K.¹

Affiliation:

1. Department of Industrial and Systems Engineering, Rutgers University, New Brunswick, NJ, USA

2. Department of Industrial Engineering & Interdisciplinary Program of Arts and Design Technology, Chonnam National University, Gwangju, Republic of Korea

3. Department of MIS, Marketing and Analytics, Rochester Institute of Technology, Rochester, NY, USA

Funder

LG Yonam Foundation

National Research Foundation of Republic of Korea

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2023.2217282

Reference36 articles.

1. Applications of Sparse Modelling and Principle Component Analysis for the Virtual Metrology of Comprehensive Multi-dimensional Quality

2. Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation

3. Loading and correlations in the interpretation of principle compenents

4. Virtual metrology of semiconductor PVD process based on combination of tree-based ensemble model

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