Modeling of continuous stirred tank reactor based on artificial neural network
Other Title(s)
نموذج لخزان مفاعل مستمر الإثارة مبني على أساس الشبكة العصبية الذكية
Author
al-Araji, Ahmad Sabah Abd al-Amir
Source
Nahrain University-College of Engineering Journal
Issue
Vol. 18, Issue 2 (31 Dec. 2015), pp.202-207, 6 p.
Publisher
Nahrain University College of Engineering
Publication Date
2015-12-31
Country of Publication
Iraq
No. of Pages
6
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
This paper presents the dynamic model identification algorithm of the continuous stirred tank reactor (CSTR) using a multi-layer perceptron (MLP) neural network topology.
The neural network approach for (CSTR) dynamic modeling is trained by using a particle swarm optimization (PSO) technique as a simple and fast training unsupervised algorithm.
Polywog wavelet activation function is used in the structure of MLP neural network.
The identification algorithm given in this paper has been proved to be reasonable and precise via Matlab simulation results in terms of fast, stable and minimum number of fitness evaluation for the CSTR modeling.
American Psychological Association (APA)
al-Araji, Ahmad Sabah Abd al-Amir. 2015. Modeling of continuous stirred tank reactor based on artificial neural network. Nahrain University-College of Engineering Journal،Vol. 18, no. 2, pp.202-207.
https://search.emarefa.net/detail/BIM-819070
Modern Language Association (MLA)
al-Araji, Ahmad Sabah Abd al-Amir. Modeling of continuous stirred tank reactor based on artificial neural network. Nahrain University-College of Engineering Journal Vol. 18, no. 2 (Dec. 2015), pp.202-207.
https://search.emarefa.net/detail/BIM-819070
American Medical Association (AMA)
al-Araji, Ahmad Sabah Abd al-Amir. Modeling of continuous stirred tank reactor based on artificial neural network. Nahrain University-College of Engineering Journal. 2015. Vol. 18, no. 2, pp.202-207.
https://search.emarefa.net/detail/BIM-819070
Data Type
Journal Articles
Language
English
Notes
Record ID
BIM-819070