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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Bibliographic Details
Published in:International Journal of Advances in Applied Sciences
Main Author: Idris S.A.; Markom M.
Format: Article
Language:English
Published: Intelektual Pustaka Media Utama 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161330110&doi=10.11591%2fijaas.v9.i2.pp117-124&partnerID=40&md5=5d932e45ec56f2eab5766c0d28a1f495
id 2-s2.0-85161330110
spelling 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
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