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Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis
المؤلفون المشاركون
Li, Xiangshun
Wei, Di
Lei, Cheng
Li, Zhiang
Wang, Wenlin
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-04-30
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Independent Component Analysis (ICA), a type of typical data-driven fault detection techniques, has been widely applied for monitoring industrial processes.
FastICA is a classical algorithm of ICA, which extracts independent components by using the Newton iteration method.
However, the choice of the initial iterative point of Newton iteration method is difficult; sometimes, selection of different initial iterative points tends to show completely different effects for fault detection.
So far, there is still no good strategy to get an ideal initial iterative point for ICA.
To solve this problem, a modified ICA algorithm based on biogeography-based optimization (BBO) called BBO-ICA is proposed for the purpose of multivariate statistical process monitoring.
The Newton iteration method is replaced with BBO here for extracting independent components.
BBO is a novel and effective optimization method to search extremes or maximums.
Comparing with the traditional intelligent optimization algorithm of particle swarm optimization (PSO) and so on, BBO behaves with stronger capability and accuracy of searching for solution space.
Moreover, numerical simulations are finished with the platform of DAMADICS.
Results demonstrate the practicability and effectiveness of BBO-ICA.
The proposed BBO-ICA shows better performance of process monitoring than FastICA and PSO-ICA for DAMADICS.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Xiangshun& Wei, Di& Lei, Cheng& Li, Zhiang& Wang, Wenlin. 2018. Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1205789
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Xiangshun…[et al.]. Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis. Mathematical Problems in Engineering No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1205789
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Xiangshun& Wei, Di& Lei, Cheng& Li, Zhiang& Wang, Wenlin. Statistical Process Monitoring with Biogeography-Based Optimization Independent Component Analysis. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1205789
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1205789
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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