Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/1691
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kıran, Mustafa Servet | - |
dc.contributor.author | Sıramkaya, Eyup | - |
dc.contributor.author | Esme, Engin | - |
dc.date.accessioned | 2022-01-30T17:32:54Z | - |
dc.date.available | 2022-01-30T17:32:54Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 1300-1884 | - |
dc.identifier.issn | 1304-4915 | - |
dc.identifier.uri | https://doi.org/10.17341/gazimmfd.890180 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.13091/1691 | - |
dc.description.abstract | Purpose: The main objective of this study is to present a novel problem, and novel methodology to solve this problem. The problem is to predict the number of students who fail the course and will join the make-up exams. Theory and Methods: The number of students who fail the course should take a make-up exam, but some of them do not join these exams due to internal or external motivations, and this causes waste of resources. Majority of voting-based extreme learning machines have been proposed to solve the problem, and the ELM parameters have been optimized by artificial bee colony algorithm. Results: The proposed approach shows better performance than the extreme learning machines in terms of classification accuracy. Conclusion: Before the scheduling make-up exams, the number of students who will join the exams should be predicted by the proposed or similar approaches in order to use resources efficiently. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Gazi Univ, Fac Engineering Architecture | en_US |
dc.relation.ispartof | Journal Of The Faculty Of Engineering And Architecture Of Gazi University | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Extreme Learning Machine | en_US |
dc.subject | Multiple Extreme Learning Machine | en_US |
dc.subject | Artificial Bee Colony | en_US |
dc.subject | Make-Up Exam | en_US |
dc.subject | Extreme Learning-Machine | en_US |
dc.title | A k-ELM approach to the prediction of number of students taking make-up exams | en_US |
dc.title.alternative | Bütünleme sınavına girecek öğrenci sayısının tahmini için k-ELM yaklaşımı | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.17341/gazimmfd.890180 | - |
dc.identifier.scopus | 2-s2.0-85119937060 | en_US |
dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
dc.identifier.volume | 37 | en_US |
dc.identifier.issue | 1 | en_US |
dc.identifier.startpage | 295 | en_US |
dc.identifier.endpage | 304 | en_US |
dc.identifier.wos | WOS:000718898200014 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.authorscopusid | 54403096500 | - |
dc.authorscopusid | 55873033200 | - |
dc.authorscopusid | 57189468408 | - |
dc.identifier.trdizinid | 1064167 | en_US |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.openairetype | Article | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.author.dept | 02.03. Department of Computer Engineering | - |
crisitem.author.dept | 02.13. Department of Software Engineering | - |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
Files in This Item:
File | Size | Format | |
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10.17341-gazimmfd.890180-1614479.pdf | 388.15 kB | Adobe PDF | View/Open |
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