Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/6062
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Efe, Mehmet Önder | - |
dc.date.accessioned | 2021-09-11T15:34:51Z | - |
dc.date.available | 2021-09-11T15:34:51Z | - |
dc.date.issued | 2010 | en_US |
dc.identifier.issn | 0965-9978 | - |
dc.identifier.issn | 1873-5339 | - |
dc.identifier.uri | https://doi.org/10.1016/j.advengsoft.2010.07.004 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/6062 | - |
dc.description.abstract | This paper presents a simulation based comparison of Multilayer Perceptron (MLP), Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Least Squares Support Vector Machines (LS-SVM) in parallel mode identification of a chemical process displaying several challenges. The paper provides a graphical analysis of the nonlinear behavior for the system under investigation, a case study of purely parallel identification scheme, the effects of noise in the training data on the prediction performance and the performance comparison of the standard approaches under limited amount of numerical data. The results have shown that the emulators utilizing the MLP structure are superior to the others in terms of predicting the system trajectories, locating the limit cycle, noise driven response and predicting the steady state conditions given only 582 pairs of training data. Furthermore, as opposed to others, with the MLP structure, these qualities disappear smoothly as the noise level is increased gradually. (C) 2010 Elsevier Ltd. All rights reserved. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier Sci Ltd | en_US |
dc.relation.ispartof | Advances In Engineering Software | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Bioreactor | en_US |
dc.subject | Identification | en_US |
dc.subject | Multilayer perceptron | en_US |
dc.subject | ANFIS | en_US |
dc.subject | Support vector machine | en_US |
dc.subject | Chemical process modeling | en_US |
dc.title | A Comparison of Networked Approximators in Parallel Mode Identification of a Bioreactor | en_US |
dc.type | Article | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Electrical and Electronics Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü | tr_TR |
dc.identifier.volume | 41 | en_US |
dc.identifier.issue | 9 | en_US |
dc.identifier.startpage | 1132 | en_US |
dc.identifier.endpage | 1147 | en_US |
dc.authorid | 0000-0002-5992-895X | - |
dc.identifier.wos | WOS:000281499100008 | en_US |
dc.identifier.scopus | 2-s2.0-78049435061 | en_US |
dc.institutionauthor | Önder Efe, Mehmet | - |
dc.identifier.doi | 10.1016/j.advengsoft.2010.07.004 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | Q1 | - |
item.openairetype | Article | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.5. Department of Electrical and Electronics Engineering | - |
Appears in Collections: | Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
CORE Recommender
SCOPUSTM
Citations
5
checked on Dec 21, 2024
WEB OF SCIENCETM
Citations
6
checked on Aug 31, 2024
Page view(s)
58
checked on Dec 23, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.