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Identification of a Typical CSTR Using Optimal Focused Time Lagged Recurrent Neural Network Model with Gamma Memory Filter
المؤلفون المشاركون
Dudul, Sanjay V.
Naikwad, S. N.
المصدر
Applied Computational Intelligence and Soft Computing
العدد
المجلد 2009، العدد 2009 (31 ديسمبر/كانون الأول 2009)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2010-01-14
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
A focused time lagged recurrent neural network (FTLR NN) with gamma memory filter is designed to learn the subtle complex dynamics of a typical CSTR process.
Continuous stirred tank reactor exhibits complex nonlinear operations where reaction is exothermic.
It is noticed from literature review that process control of CSTR using neuro-fuzzy systems was attempted by many, but optimal neural network model for identification of CSTR process is not yet available.
As CSTR process includes temporal relationship in the input-output mappings, time lagged recurrent neural network is particularly used for identification purpose.
The standard back propagation algorithm with momentum term has been proposed in this model.
The various parameters like number of processing elements, number of hidden layers, training and testing percentage, learning rule and transfer function in hidden and output layer are investigated on the basis of performance measures like MSE, NMSE, and correlation coefficient on testing data set.
Finally effects of different norms are tested along with variation in gamma memory filter.
It is demonstrated that dynamic NN model has a remarkable system identification capability for the problems considered in this paper.
Thus FTLR NN with gamma memory filter can be used to learn underlying highly nonlinear dynamics of the system, which is a major contribution of this paper.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Naikwad, S. N.& Dudul, Sanjay V.. 2010. Identification of a Typical CSTR Using Optimal Focused Time Lagged Recurrent Neural Network Model with Gamma Memory Filter. Applied Computational Intelligence and Soft Computing،Vol. 2009, no. 2009, pp.1-7.
https://search.emarefa.net/detail/BIM-467956
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Naikwad, S. N.& Dudul, Sanjay V.. Identification of a Typical CSTR Using Optimal Focused Time Lagged Recurrent Neural Network Model with Gamma Memory Filter. Applied Computational Intelligence and Soft Computing No. 2009 (2009), pp.1-7.
https://search.emarefa.net/detail/BIM-467956
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Naikwad, S. N.& Dudul, Sanjay V.. Identification of a Typical CSTR Using Optimal Focused Time Lagged Recurrent Neural Network Model with Gamma Memory Filter. Applied Computational Intelligence and Soft Computing. 2010. Vol. 2009, no. 2009, pp.1-7.
https://search.emarefa.net/detail/BIM-467956
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-467956
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