Forecast combination approach with meta-fuzzy functions for forecasting the number of immigrants within the maritime line security project in Turkey

Basit Öğe Kaydı
dc.authorid0000-0003-0811-8217
dc.authorid0000-0001-8796-5101
dc.authorid0000-0001-6414-508X
dc.contributor.authorCevik, Fatma Carman
dc.contributor.authorGever, Basak
dc.contributor.authorTak, Nihat
dc.contributor.authorKhaniyev, Tahir
dc.date.accessioned2026-02-12T21:04:57Z
dc.date.available2026-02-12T21:04:57Z
dc.date.issued2023
dc.departmentBursa Teknik Üniversitesi
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.
dc.description.sponsorshipMinistry of Interior of Republic of Turkey and The Scientific and Technological Research Council of Turkey (TUBITAK)
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.
dc.identifier.doi10.1007/s00500-022-07800-7
dc.identifier.endpage2535
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.issue5
dc.identifier.pmid36628119
dc.identifier.scopus2-s2.0-85145670808
dc.identifier.scopusqualityQ1
dc.identifier.startpage2509
dc.identifier.urihttps://doi.org/10.1007/s00500-022-07800-7
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6739
dc.identifier.volume27
dc.identifier.wosWOS:000909478800002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofSoft Computing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260212
dc.subjectImmigration
dc.subjectForecasting
dc.subjectMeta-fuzzy functions
dc.subjectLong short-term memory
dc.subjectFuzzy inference systems and Artificial neural network
dc.titleForecast combination approach with meta-fuzzy functions for forecasting the number of immigrants within the maritime line security project in Turkey
dc.typeArticle

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