Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism
المؤلفون المشاركون
Chun, Semin
Maruta, Ichiro
Sugie, Toshiharu
Chae, Minji
Kim, Tae-Hyoung
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-03-27
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems.
To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established.
A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail.
Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO) is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed.
This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process.
This is one of the distinguishing features of the proposed method.
The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria.
Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Kim, Tae-Hyoung& Maruta, Ichiro& Sugie, Toshiharu& Chun, Semin& Chae, Minji. 2017. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190401
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Kim, Tae-Hyoung…[et al.]. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism. Mathematical Problems in Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1190401
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Kim, Tae-Hyoung& Maruta, Ichiro& Sugie, Toshiharu& Chun, Semin& Chae, Minji. Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190401
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1190401
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر