https://hdl.handle.net/20.500.12809/129 Tue, 07 Apr 2026 10:19:36 GMT 2026-04-07T10:19:36Z https://hdl.handle.net/20.500.12809/9230 Dynamic aggregation operators and Einstein operations based on interval-valued picture hesitant fuzzy information and their applications in multi-period decision making Kamacı, Hüseyin; Petchimuthu, Subramanian; Akçetin, Eyüp The traditional picture hesitant fuzzy aggregation operators are generally suitable for aggregating information acquired in the form of picture hesitant fuzzy numbers, but they will fail in dealing with interval-valued picture hesitant fuzzy information. In this paper, we describe the notion of interval-valued picture hesitant fuzzy set and the operational laws of interval-valued picture hesitant fuzzy variables. Moreover, we derive some dynamic interval-valued picture hesitant fuzzy aggregation operators (based on Einstein operators) to aggregate the interval-valued picture hesitant fuzzy information collected at different periods. Some desirable properties of these aggregation operators are discussed in detail. In addition, we develop the approaches to tackle the multi-period decision-making problems, where all decision information takes the form of interval-valued picture hesitant fuzzy information collected at different periods. In an attempt to illustrate the applications of the proposed approaches, two numerical examples are given to measure the impact of Coronavirus Disease 2019 (COVID-19) in daily life and to identify the optimal investment opportunity. Finally, a comparative analysis of the proposed and existing studies are conducted to demonstrate the effectiveness of the proposed approaches. The presented interval-valued picture hesitant fuzzy operations, aggregation operators, and decision-making approaches can widely apply to dynamic decision analysis and multi-stage decision analysis in real life. Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/20.500.12809/9230 2021-01-01T00:00:00Z https://hdl.handle.net/20.500.12809/8051 Improving Service Processes and the Library Quality Service with Data Mining Method Yurtay, Yüksel; Çiftci, Özgür; Akçetin, Eyüp İçinde bulunduğumuz dijital çağda tüketicileri bilgilerini toplayan İşletmeler; müşterilerine daha iyi hizmet vermek ya da yeni pazar alanları açabilmek adına tüketici bilgilerinden çıkarımlar yapmaktadır. Bu işlemlerden sonuçlar elde edebilmek için de yapay zeka teknikleri ile birlikte veri madenciliği yöntem ve algoritmaları kullanmaktadırlar. Yoğun rekabet ortamında veri madenciliği yöntemleri hizmet üreten süreçlerde de etkin bir biçimde kullanılmaktadır. Müşteri ilişkileri bağlamında bu teknikler kütüphane süreçlerinin iyileştirilmesinde ve hizmet kalitesinin artırılmasında veri madenciliği yöntemlerinden yararlanılmaktadır. Bu çalışma kapsamında İlk olarak kullanıcı profiline ve arama geçmişine dayalı kümelemeler gerçekleştirilmiştir. İkinci aşamasında kümeler içerisindeki okuyucu taleplerindeki frekanslar belirlenerek kütüphane hizmetlerinin yapılanmasına dönük değerlendirmeler yapılmıştır. Bu çalışmanın veri setini belirli bir zaman aralığında bir kamu üniversitesinin veri tabanından alınan veriler oluşturmaktadır. Çalışmada yöntem olarak söz konusu kütüphanenin verilerine veri madenciliği yöntemlerinden kümeleme ve apriori algoritması kullanılmıştır. Sonuç olarak kütüphane verileri üzerinde uygulanan veri madenciliği algoritmaları ile kütüphanede verilen hizmet süreçlerinin ve bu hizmetlerin kalitesinin iyileştirilmesi için okuyucu profillerinin tanımlanması, dönemsel değişen okuyucu taleplerinin görüntülenmesi ve okuyucuların kütüphane etkileşimleri belirlenmiştir. Sonraki çalışmalarda farklı üniversitelerden kütüphane verileri alınarak daha farklı araştırmalar, kıyaslamalar yapılabilir ve farklı sonuçlar elde edilebilir. Aynı zamanda farklı kütüphanelerin okuyucuları için çalışmalar tekrarlanarak sonuçlar değerlendirilebilir. Benzer çalışmalarda, veri miktarı ve zaman aralığının, sonuçlar üzerinde etkili olabilir.; In this digital age, businesses that collect consumer information; provide better service to its customers or new market areas in the name of consumer information from the open mining, artificial intelligence techniques, methods and algorithms in conjunction with data mining are used in order to be able to get the results of these operations.Data mining methods in an intensive competition environment in the service-producing process, are being used effectively. For customer relations in the context of these techniques in improving library processes and in improving the quality of service data mining method is utilized.The data aim-based of this study was to set a specific time range of the data that is received from a public University. Study of the library data in question required data mining methods of clustering and the apriori algorithm.As a result, the library data are implemented on data mining algorithms in the library with the given service processes and improvement of the quality of these services being the defining periodic changing of profile reader to reader demands and determined display and readers library interactions. Subsequent studies based on data from different universities library may lead too to different research, comparisons, and therefore different results. At the same time, the results of repeated studies for the readers of different library can be evaluated. İn similar studies, the amount of data and the range of time can be effective on the results too. Mon, 01 Jan 2018 00:00:00 GMT https://hdl.handle.net/20.500.12809/8051 2018-01-01T00:00:00Z https://hdl.handle.net/20.500.12809/364 New analysis and application of fractional order Schrodinger equation using with Atangana-Batogna numerical scheme Akçetin, Eyüp; Koca, İlknur; Kılıç, Muhammet Burak In this work, an analytical approximation to the solution of Schrodinger equation has been provided. The fractional derivative used in this equation is the Caputo derivative. The existence and uniqueness conditions of solutions for the proposed model are derived based on the power law. While solving the fractional order Schrodinger equation, Atangana-Batogna numerical method is presented for fractional order equation. We obtain an efficient recurrence relation for solving these kinds of equations. To illustrate the usefulness of the numerical scheme, the numerical simulations are presented. The results show that the numerical scheme is very effective and simple. WOS: 000561871900001 Wed, 01 Jan 2020 00:00:00 GMT https://hdl.handle.net/20.500.12809/364 2020-01-01T00:00:00Z