Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/10325
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dc.contributor.authorÇevik, Fatma Carman-
dc.contributor.authorGever, Başak-
dc.contributor.authorTak, Nihat-
dc.contributor.authorKhaniyev, Tahir-
dc.date.accessioned2023-04-16T10:00:17Z-
dc.date.available2023-04-16T10:00:17Z-
dc.date.issued2023-
dc.identifier.issn1432-7643-
dc.identifier.issn1433-7479-
dc.identifier.urihttps://doi.org/10.1007/s00500-022-07800-7-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/10325-
dc.description.abstractIn this study, forecasting the number of immigrants on the Turkey's maritime line for use in a national security project carried out by Turkish Government within the scope of fight against uncontrolled immigration is discussed for the first time. Handling with the immigration problem is one of the biggest concerns of Turkey as unsupervised immigration can adversely affect the demographic and economic structure of the country. Precautions are needed as the short-, medium- and long-term impacts of undetected immigrants on the country's ecosystem are unpredictable, but due to the uncertainties inherent in immigration, the cost of using government resources such as patrol vehicles to capture undocumented immigrants can be extremely high. In order to both minimize the expenditure problem and keep immigration under control by providing a proper scan, forecasting the number of immigrants on the maritime line route is seen as an important problem and studied by probabilistic and non-probabilistic models. Since the data for 2020 and 2021 could not be attained yet due to COVID-19, in order to obtain forecasts and compare actual observations for 2019, which is the primarily focus of the research in this study, the dataset of interest on the number of daily immigrants between years 2016 and 2019 is obtained from Turkish Coast Guard Command within Ministry of Interior of Republic of Turkey. To obtain the most accurate forecasts, seven distinguished forecasting methods, from simple to complex, are implemented. Then, the forecast combination approach with meta-fuzzy functions which combines all methods is proposed. Consequently, the forecasting results are acquired and evaluated by using R. The evaluation of the results is made by using widely considered measurement accuracy metric root mean square error. According to the final assessments, the proposed approach gives more accurate forecasting results for the expected number of immigrants on the Turkey's maritime line and these results become an input to the national security project.en_US
dc.description.sponsorshipMinistry of Interior of Republic of Turkey and The Scientific and Technological Research Council of Turkey (TUBITAK)en_US
dc.description.sponsorshipI would like to thank to Turkish Coast Guard Command within Ministry of Interior of Republic of Turkey and The Scientific and Technological Research Council of Turkey (TUBITAK) for their support.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSoft Computingen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectImmigrationen_US
dc.subjectForecastingen_US
dc.subjectMeta-fuzzy functionsen_US
dc.subjectLong short-term memoryen_US
dc.subjectFuzzy inference systems and Artificial neural networken_US
dc.subjectArimaen_US
dc.subjectAnfisen_US
dc.subjectModelen_US
dc.subjectAnnen_US
dc.titleForecast Combination Approach With Meta-Fuzzy Functions for Forecasting the Number of Immigrants Within the Maritime Line Security Project in Turkeyen_US
dc.typeArticleen_US
dc.departmentTOBB ETÜen_US
dc.identifier.volume27en_US
dc.identifier.issue5en_US
dc.identifier.startpage2509en_US
dc.identifier.endpage2535en_US
dc.authoridGEVER, BASAK/0000-0001-6414-508X-
dc.authoridCarman Cevik, Fatma/0000-0003-0811-8217-
dc.identifier.wosWOS:000909478800002en_US
dc.identifier.scopus2-s2.0-85145670808en_US
dc.institutionauthor-
dc.identifier.pmid36628119en_US
dc.identifier.doi10.1007/s00500-022-07800-7-
dc.authorwosidTak, Nihat/AAG-2425-2019-
dc.authorscopusid6507957120-
dc.authorscopusid55255755600-
dc.authorscopusid57194529021-
dc.authorscopusid7801652544-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.4. Department of Industrial Engineering-
Appears in Collections:PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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