Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network

Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network

A novel comparison study based on a radial basis function neural network (RBFNN) and Response Surface Methodology (RSM) is proposed to predict the conversion rate (yield) of the experimental data for PNVCL polymerization. A statistical and optimization model was performing to show the effect of each...

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Main Authors: Marwah Noori, Mohammed, Kamal, Yusoh, Jun Haslinda, Haji Shariffuddin
Format: Conference or Workshop Item
Language:English
Published: EDP Sciences 2018
Subjects:
TP Chemical technology
Online Access:http://umpir.ump.edu.my/id/eprint/23251/
http://umpir.ump.edu.my/id/eprint/23251/
http://umpir.ump.edu.my/id/eprint/23251/1/Parametric%20Optimization%20of%20the%20Poly%20%28Nvinylcaprolactam%29%20%28PNVCL%29.pdf
id ump-23251
recordtype eprints
spelling ump-232512018-12-14T09:06:43Z http://umpir.ump.edu.my/id/eprint/23251/ Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network Marwah Noori, Mohammed Kamal, Yusoh Jun Haslinda, Haji Shariffuddin TP Chemical technology A novel comparison study based on a radial basis function neural network (RBFNN) and Response Surface Methodology (RSM) is proposed to predict the conversion rate (yield) of the experimental data for PNVCL polymerization. A statistical and optimization model was performing to show the effect of each parameter and their interactions on the conversion rate. The influence of the time, polymerization temperature, initiator concentration and concentration of the monomer were studied. The results obtained in this study indicate that the RBFNN was an effective method for predicting the conversion rate. The time of the PNVCL polymerization as well as the concentration of the monomer show the maximum effect on the conversion rate. In addition, compared with the RSM method, the RBFNN showed better conversion rate comparing with the experimental data. EDP Sciences 2018 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/23251/1/Parametric%20Optimization%20of%20the%20Poly%20%28Nvinylcaprolactam%29%20%28PNVCL%29.pdf Marwah Noori, Mohammed and Kamal, Yusoh and Jun Haslinda, Haji Shariffuddin (2018) Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network. In: MATEC Web of Conferences: UTP-UMP-VIT Symposium on Energy Systems 2018 (SES 2018), September 18-19, 2018 , Universiti Malaysia Pahang. pp. 1-7., 225 (02023). ISSN 2261-236X https://doi.org/10.1051/matecconf/201822502023
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
Marwah Noori, Mohammed
Kamal, Yusoh
Jun Haslinda, Haji Shariffuddin
Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network
description A novel comparison study based on a radial basis function neural network (RBFNN) and Response Surface Methodology (RSM) is proposed to predict the conversion rate (yield) of the experimental data for PNVCL polymerization. A statistical and optimization model was performing to show the effect of each parameter and their interactions on the conversion rate. The influence of the time, polymerization temperature, initiator concentration and concentration of the monomer were studied. The results obtained in this study indicate that the RBFNN was an effective method for predicting the conversion rate. The time of the PNVCL polymerization as well as the concentration of the monomer show the maximum effect on the conversion rate. In addition, compared with the RSM method, the RBFNN showed better conversion rate comparing with the experimental data.
format Conference or Workshop Item
author Marwah Noori, Mohammed
Kamal, Yusoh
Jun Haslinda, Haji Shariffuddin
author_facet Marwah Noori, Mohammed
Kamal, Yusoh
Jun Haslinda, Haji Shariffuddin
author_sort Marwah Noori, Mohammed
title Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network
title_short Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network
title_full Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network
title_fullStr Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network
title_full_unstemmed Parametric Optimization of the Poly (Nvinylcaprolactam) (PNVCL) Thermoresponsive Polymers Synthesis by the Response Surface Methodology and Radial Basis Function neural network
title_sort parametric optimization of the poly (nvinylcaprolactam) (pnvcl) thermoresponsive polymers synthesis by the response surface methodology and radial basis function neural network
publisher EDP Sciences
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/23251/
http://umpir.ump.edu.my/id/eprint/23251/
http://umpir.ump.edu.my/id/eprint/23251/1/Parametric%20Optimization%20of%20the%20Poly%20%28Nvinylcaprolactam%29%20%28PNVCL%29.pdf
first_indexed 2023-09-18T22:34:43Z
last_indexed 2023-09-18T22:34:43Z
_version_ 1777416519297269760

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