Home | About us | Editorial board | Search | Ahead of print | Current issue | Archives | Submit article | Instructions | Subscribe | Contacts | Advertise | Login 
  Official website of M M University Mullana      
   
ARTICLE
Year : 2013  |  Volume : 3  |  Issue : 2  |  Page : 76-81

Control chart patterns recognition using optimized adaptive neuro-fuzzy inference system and wavelet analysis


Department of Engineering, Minoodasht Branch, islamic Azad University, Minoodasht, Iran

Correspondence Address:
Amir Bahador Bayat
Department of Engineering, Minoodasht Branch, islamic Azad University, Minoodasht
Iran
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0976-8580.113042

Rights and Permissions

Unnatural patterns in the control charts can be associated with a specific set of assignable causes for process variation. Hence, pattern recognition is very useful in identifying process problem. In this study, we have developed an expert system that we called an expert system for control chart patterns recognition for recognition of the common types of control chart patterns (CCPs). The proposed system includes three main modules: The feature extraction module, the classifier module and the optimization module. In the feature extraction module, the multi-resolution wavelets (MRW) are proposed as the effective features for representation of CCPs. In the classifier module, the adaptive neuro-fuzzy inference system (ANFIS) is investigated. In ANFIS training, the vector of radius has a very important role for its recognition accuracy. Therefore, in the optimization module, cuckoo optimization algorithm is proposed for finding optimum vector of radius. Simulation results show that the proposed system has high recognition accuracy.


[PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed1423    
    Printed74    
    Emailed0    
    PDF Downloaded1314    
    Comments [Add]    
    Cited by others 3    

Recommend this journal