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

dc.contributor.authorTAK, NİHAT
dc.contributor.authorsCevik F. C., Gever B., Tak N., Khaniyev T.
dc.date.accessioned2023-03-06T11:13:22Z
dc.date.accessioned2026-01-11T19:26:19Z
dc.date.available2023-03-06T11:13:22Z
dc.date.issued2023-03-01
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.identifier.citationCevik F. C., Gever B., Tak N., Khaniyev T., "Forecast combination approach with meta-fuzzy functions for forecasting the number of immigrants within the maritime line security project in Turkey", SOFT COMPUTING, cilt.27, sa.5, ss.2509-2535, 2023
dc.identifier.doi10.1007/s00500-022-07800-7
dc.identifier.endpage2535
dc.identifier.issn1432-7643
dc.identifier.issue5
dc.identifier.startpage2509
dc.identifier.urihttps://hdl.handle.net/11424/287181
dc.identifier.volume27
dc.language.isoeng
dc.relation.ispartofSOFT COMPUTING
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBilgisayar Bilimleri
dc.subjectAlgoritmalar
dc.subjectBilgisayar Grafiği
dc.subjectMühendislik ve Teknoloji
dc.subjectComputer Sciences
dc.subjectalgorithms
dc.subjectComputer Graphics
dc.subjectEngineering and Technology
dc.subjectBİLGİSAYAR BİLİMİ, YAPAY ZEKA
dc.subjectBilgisayar Bilimi
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBİLGİSAYAR BİLİMİ, İNTERDİSİPLİNER UYGULAMALAR
dc.subjectCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
dc.subjectCOMPUTER SCIENCE
dc.subjectEngineering, Computing & Technology (ENG)
dc.subjectCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
dc.subjectYer Bilimlerinde Bilgisayarlar
dc.subjectBilgisayarla Görme ve Örüntü Tanıma
dc.subjectBilgisayar Bilimi Uygulamaları
dc.subjectBilgisayar Grafikleri ve Bilgisayar Destekli Tasarım
dc.subjectYapay Zeka
dc.subjectBilgisayar Bilimi (çeşitli)
dc.subjectGenel Bilgisayar Bilimi
dc.subjectFizik Bilimleri
dc.subjectComputers in Earth Sciences
dc.subjectComputer Vision and Pattern Recognition
dc.subjectComputer Science Applications
dc.subjectComputer Graphics and Computer-Aided Design
dc.subjectArtificial Intelligence
dc.subjectComputer Science (miscellaneous)
dc.subjectGeneral Computer Science
dc.subjectPhysical Sciences
dc.subjectImmigration
dc.subjectForecasting
dc.subjectMeta-fuzzy functions
dc.subjectLong short-term memory
dc.subjectFuzzy inference systems and Artificial neural network
dc.subjectARIMA
dc.subjectANFIS
dc.subjectMODEL
dc.subjectANN
dc.titleForecast combination approach with meta-fuzzy functions for forecasting the number of immigrants within the maritime line security project in Turkey
dc.typearticle
dspace.entity.typePublication

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