Applying emerging soft computing approaches to control chart pattern recognition for an SPC–EPC process-Reference-Cited by-同舟云学术

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Applying emerging soft computing approaches to control chart pattern recognition for an SPC–EPC process

Published:2016-08 Issue: Volume:201 Page:19-28
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Shao Yuehjen E.,Chiu Chih-Chou

Funder

Ministry of Science and Technology, Republic of China (Taiwan)

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference58 articles.

1. Economic control of quality of manufactured product;Shewhart,1931

2. A neural network ensemble model for on-line monitoring of process mean and variance shifts in correlated processes;Wu;Expert Syst. Appl.,2010

3. An augmented neural network classification approach to detecting mean shifts in correlated manufacturing process parameters;Zobel;Int. J. Prod. Res.,2004

4. Real-time recognition of control chart patterns in autocorrelated processes using a learning vector quantization network-based approach;Guh;Int. J. Prod. Res.,2008

5. Joint estimation: SPC method for short-run autocorrelated data;Wright;J. Qual. Technol.,2001

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3. Control chart pattern recognition using spectral clustering technique and support vector machine under gamma distribution;Computers & Industrial Engineering;2022-09

4. Research on Pattern Recognition Performance of Control Chart Based on Deep Learning;2022 Global Conference on Robotics, Artificial Intelligence and Information Technology (GCRAIT);2022-07

5. Concurrent Control Chart Pattern Recognition: A Systematic Review;Mathematics;2022-03-15

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