Enhancing the detection ability of control charts in profile monitoring by adding RBF ensemble model
Author:
Funder
Ferdowsi University of Mashhad
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-06962-7.pdf
Reference64 articles.
1. Zaman M, Hassan A (2019) Improved statistical features-based control chart patterns recognition using ANFIS with fuzzy clustering. Neural Comput Appl 31:5935–5949
2. Montgomery DC (2019) Introduction to statistical quality control. Wiley & Sons, New York
3. Salmasnia A, Rahimi A, Abdzadeh B (2019) An integration of NSGA-II and DEA for economic–statistical design of T2-Hotelling control chart with double warning lines. Neural Comput Appl 31:1173–1194
4. Yeganeh A, Pourpanah F, Shadman A (2021) An ANN-based ensemble model for change point estimation in control charts. Appl Soft Comput 110:107604
5. Das P, Banerjee I (2011) An hybrid detection system of control chart patterns using cascaded SVM and neural network–based detector. Neural Comput Appl 20:287–296
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