Issues in development of artificial neural network-based control chart pattern recognition schemes
Control chart pattern recognition has become an active area of research since late 1980s. Much progress has been made, in which there are trends to heighten the performance of artificial neural network (ANN)-based control chart pattern recognition schemes through feature-based and wavelet-denoise in...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
EuroJournals Publishing
2010
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4478/1/AJ%202018%20%2891%29.pdf http://eprints.uthm.edu.my/4478/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1833417609741074432 |
|---|---|
| author | Masood, Ibrahim Hassan, Adnan |
| author_facet | Masood, Ibrahim Hassan, Adnan |
| author_sort | Masood, Ibrahim |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Control chart pattern recognition has become an active area of research since late 1980s. Much progress has been made, in which there are trends to heighten the performance of artificial neural network (ANN)-based control chart pattern recognition schemes through feature-based and wavelet-denoise input representation techniques, and through modular and integrated recognizer designs. There is also a trend to enhance it’s capability for monitoring and diagnosing multivariate process shifts. However, there is a lack of literature providing a critical review on the issues associated to such advances. The purpose of this paper is to highlight research direction, as well as to present a summary of some updated issues in the development of ANN-based control chart pattern recognition schemes as being addressed by the frontiers in this area. The issues highlighted in this paper are highly related to input data and process patterns, input representation, recognizer design and training, and multivariate process monitoring and diagnosis. Such issues could be useful for new researchers as a starting point to facilitate further improvement in this area. |
| format | Article |
| id | my.uthm.eprints-4478 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2010 |
| publisher | EuroJournals Publishing |
| record_format | eprints |
| spelling | my.uthm.eprints-44782021-12-07T04:04:18Z http://eprints.uthm.edu.my/4478/ Issues in development of artificial neural network-based control chart pattern recognition schemes Masood, Ibrahim Hassan, Adnan T Technology (General) TJ Mechanical engineering and machinery TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television Control chart pattern recognition has become an active area of research since late 1980s. Much progress has been made, in which there are trends to heighten the performance of artificial neural network (ANN)-based control chart pattern recognition schemes through feature-based and wavelet-denoise input representation techniques, and through modular and integrated recognizer designs. There is also a trend to enhance it’s capability for monitoring and diagnosing multivariate process shifts. However, there is a lack of literature providing a critical review on the issues associated to such advances. The purpose of this paper is to highlight research direction, as well as to present a summary of some updated issues in the development of ANN-based control chart pattern recognition schemes as being addressed by the frontiers in this area. The issues highlighted in this paper are highly related to input data and process patterns, input representation, recognizer design and training, and multivariate process monitoring and diagnosis. Such issues could be useful for new researchers as a starting point to facilitate further improvement in this area. EuroJournals Publishing 2010 Article PeerReviewed text en http://eprints.uthm.edu.my/4478/1/AJ%202018%20%2891%29.pdf Masood, Ibrahim and Hassan, Adnan (2010) Issues in development of artificial neural network-based control chart pattern recognition schemes. European Journal of Scientific Research, 39 (9). pp. 336-355. ISSN 1450-216X |
| spellingShingle | T Technology (General) TJ Mechanical engineering and machinery TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television Masood, Ibrahim Hassan, Adnan Issues in development of artificial neural network-based control chart pattern recognition schemes |
| title | Issues in development of artificial neural network-based control chart pattern recognition schemes |
| title_full | Issues in development of artificial neural network-based control chart pattern recognition schemes |
| title_fullStr | Issues in development of artificial neural network-based control chart pattern recognition schemes |
| title_full_unstemmed | Issues in development of artificial neural network-based control chart pattern recognition schemes |
| title_short | Issues in development of artificial neural network-based control chart pattern recognition schemes |
| title_sort | issues in development of artificial neural network-based control chart pattern recognition schemes |
| topic | T Technology (General) TJ Mechanical engineering and machinery TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television |
| url | http://eprints.uthm.edu.my/4478/1/AJ%202018%20%2891%29.pdf http://eprints.uthm.edu.my/4478/ |
| url_provider | http://eprints.uthm.edu.my/ |