Overview of soft intelligent computing technique for supercritical fluid extraction
Optimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent...
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Intelektual Pustaka Media Utama
2020
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2-s2.0-85161330110 Idris S.A.; Markom M. Overview of soft intelligent computing technique for supercritical fluid extraction 2020 International Journal of Advances in Applied Sciences 9 2 10.11591/ijaas.v9.i2.pp117-124 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161330110&doi=10.11591%2fijaas.v9.i2.pp117-124&partnerID=40&md5=5d932e45ec56f2eab5766c0d28a1f495 Optimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent factors. Recently there are growing interest in applying smart system or artificial technique to model and simulate a chemical process and also to predict, compute, classify and optimize as well as for process control. This system works by generalizing the experimental result and the process behavior and finally predict and estimate the problem. This smart system is a major assistance in the development of process from laboratory to pilot or industrial. The main advantage of intelligent systems is that the predictions can be performed easily, fast, and accurate way, which physical models unable to do. This paper shares several works that have been utilizing intelligent systems for modeling and simulating the supercritical fluid extraction process. © 2020, Intelektual Pustaka Media Utama. All rights reserved. Intelektual Pustaka Media Utama 22528814 English Article All Open Access; Gold Open Access; Green Open Access |
author |
Idris S.A.; Markom M. |
spellingShingle |
Idris S.A.; Markom M. Overview of soft intelligent computing technique for supercritical fluid extraction |
author_facet |
Idris S.A.; Markom M. |
author_sort |
Idris S.A.; Markom M. |
title |
Overview of soft intelligent computing technique for supercritical fluid extraction |
title_short |
Overview of soft intelligent computing technique for supercritical fluid extraction |
title_full |
Overview of soft intelligent computing technique for supercritical fluid extraction |
title_fullStr |
Overview of soft intelligent computing technique for supercritical fluid extraction |
title_full_unstemmed |
Overview of soft intelligent computing technique for supercritical fluid extraction |
title_sort |
Overview of soft intelligent computing technique for supercritical fluid extraction |
publishDate |
2020 |
container_title |
International Journal of Advances in Applied Sciences |
container_volume |
9 |
container_issue |
2 |
doi_str_mv |
10.11591/ijaas.v9.i2.pp117-124 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161330110&doi=10.11591%2fijaas.v9.i2.pp117-124&partnerID=40&md5=5d932e45ec56f2eab5766c0d28a1f495 |
description |
Optimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent factors. Recently there are growing interest in applying smart system or artificial technique to model and simulate a chemical process and also to predict, compute, classify and optimize as well as for process control. This system works by generalizing the experimental result and the process behavior and finally predict and estimate the problem. This smart system is a major assistance in the development of process from laboratory to pilot or industrial. The main advantage of intelligent systems is that the predictions can be performed easily, fast, and accurate way, which physical models unable to do. This paper shares several works that have been utilizing intelligent systems for modeling and simulating the supercritical fluid extraction process. © 2020, Intelektual Pustaka Media Utama. All rights reserved. |
publisher |
Intelektual Pustaka Media Utama |
issn |
22528814 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access; Green Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1820775463393427456 |