Performance of Machine Learning Algorithms for Class-Imbalanced Process Fault Detection Problems-Reference-Cited by-同舟云学术

Performance of Machine Learning Algorithms for Class-Imbalanced Process Fault Detection Problems

Published:2016-11 Issue:4 Volume:29 Page:436-445
ISSN:0894-6507
Container-title:IEEE Transactions on Semiconductor Manufacturing
language:
Short-container-title:IEEE Trans. Semicond. Manufact.

Author:

Lee Taehyung,Lee Ki Bum,Kim Chang Ouk^ORCID

Funder

Technology Innovation Program (Development of Big Data-Based Analysis and Control Platform for Semiconductor Manufacturing Plants) through the Ministry of Trade, Industry and Energy, South Korea

Global Ph.D. Fellowship Program through the National Research Foundation of Korea (NRF) by the Ministry of Education

NRF Grant by the Korean Government (MSIP)

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Condensed Matter Physics,Electronic, Optical and Magnetic Materials

Link

http://xplorestaging.ieee.org/ielx7/66/7587442/07549079.pdf?arnumber=7549079

Cited by 53 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel decision support system based on computational intelligence and machine learning: Towards zero-defect manufacturing in injection molding;Journal of Industrial Information Integration;2024-07

2. A conceptual framework for machine learning algorithm selection for predictive maintenance;Engineering Applications of Artificial Intelligence;2024-07

3. Mitigating class imbalance in heart disease detection with machine learning;Multimedia Tools and Applications;2024-06-27

4. Class imbalanced problem: Taxonomy, open challenges, applications and state-of-the-art solutions;China Communications;2024

5. An Imbalanced Data Classification Method Based on Hybrid Resampling and Fine Cost Sensitive Support Vector Machine;Computers, Materials & Continua;2024