Sürdürülebilir Kalkınma Amaçları

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Yazarlar

• Altuntas, S.(1)
• Büşra Pörge(1)
• Dayi, Faruk(1)
• Dereli, T.(1)
• Erdogdu, Aylin(1)
• Esmer, Yusuf(1)
• Ganji, Farshad(1)
• Selim, H.(1)
• Yildiz, Ferah(1)

• MakaleAçık Erişim2026Scopus SJRQ1/r/bayburt/11561
  Optimizing Budget Allocation for Digital Health Investments Using Metaheuristic Algorithms: A Cost–Impact Analysis for Public Health Systems

  Dayi, Faruk; Erdogdu, Aylin; Esmer, Yusuf; Yildiz, Ferah; Ganji, Farshad

  Background: In the era of digital transformation, public health systems increasingly rely on digital technologies to improve accessibility, efficiency, and patient outcomes. However, policymakers face significant challenges in allocating limited resources across competing digital health investments characterized by uncertainty and dynamic impacts. Methods: This study introduces the Adaptive Impact–Cost Optimization Theory (AICOT), a hybrid framework integrating fuzzy logic and genetic algorithms to optimize digital health investment portfolios. The model defines the Investment Priority Score (IPS) as a function of cost, expected impact, and implementation feasibility, enabling structured evaluation under uncertainty. A fuzzy inference system with centroid-based defuzzification is used to convert qualitative assessments into quantitative scores, while optimization techniques identify optimal portfolios across different fiscal scenarios. The empirical analysis covers 15 OECD countries (2018–2024) using publicly available datasets. Sensitivity analyses assess robustness under inflation, cost shocks, and changing system priorities. Results: The findings show that blended investment strategies combining routine digital health tools with pandemic-oriented infrastructures yield the highest resilience-adjusted efficiency. Results remain stable across sensitivity scenarios, with pandemic surveillance consistently ranking as a top priority even under increased cost conditions. The model effectively captures cross-country heterogeneity, demonstrating adaptability to different levels of digital maturity. Conclusions: AICOT provides a transparent and policy-relevant decision-support framework that improves resource allocation efficiency and reduces unnecessary expenditures. These contributions support long-term financial sustainability and align with global health objectives, including Universal Health Coverage and Sustainable Development Goal 3 (Good Health and Well-being).

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  AtıfScopus1·WoS1·OpenAlex1

  İncele
• Yüksek Lisans TeziAçık Erişim2019/r/bayburt/17034
  Bulanık mantık yardımıyla üç eksenli beton basınç modellerinin güvenilirliklerinin araştırılması

  Büşra Pörge

  Üç eksenli beton basınç modelleri, betonun doğrusal olmayan analizlerindeki davranışlarının gerçekçi olarak modellenmesinde kullanılmaktadır. Teknik literatürde birçok matematiksel modele rastlamak mümkündür. Model sayısının fazlalığı, farklı beton dayanım sınıfları ve farklı yanal basınç düzeylerinde doğru model seçiminde tereddütler yaşanmaktadır. Bu nedenle bu modellerin 23 farklı beton dayanım sınıfı ve 5 farklı yanal basınç düzeyinde güvenilirliklerinin araştırılması bu çalışmanın ana amacını oluşturmaktadır. Bu amacı gerçekleştirmek için güvenilirlik çalışmalarında en hassas yaklaşım olan Monte Carlo Simülasyonu kullanılmıştır. Bu Simülasyon için gerekli olan çok sayıdaki deneysel veri; yapay zekâ yöntemlerinden olan Bulanık Mantık yöntemi vasıtasıyla yapay olarak üretilmiştir. Analizler sonucunda elde edilen güvenilirlik indeksleri yardımıyla tüm modellere ait güvenilirlikler grafiklerle değerlendirilmiş ve nihayetinde modellerin güvenli olarak kullanılabilecekleri yanal gerilme düzeyi ve beton basınç sınıfları çizelgeler ile verilmiştir.

  İncele
• BildiriAçık Erişim2013Scopus SJRQ2/r/bayburt/14048
  Fuzzy weighted association rule based solution approaches to facility layout problem in cellular manufacturing system

  Altuntas, S.; Dereli, T.; Selim, H.

  This study aims to propose new solution approaches based on fuzzy weighted association rules for facility layout problem in a cellular manufacturing system. The facility layout problem under concern has two important aspects, namely; fuzzy product route and fuzzy machine weight. Number of machine types as well as the number of machines in each type is determined in order to define a fuzzy product route. A fuzzy set is then assigned for each machine type to match them with appropriate products. Alternative routes for each product and machine weights are defined by fuzzy functions. Market demand is also used to assign weights to the machines. Three solution approaches, namely fuzzy weighted association rule mining (FWARM), Gyenesei's weighted quantitative association rules (WQAR) and normalised weighted association rule mining (NWARM) based approaches, are proposed in this study. To the authors' best knowledge, this is the first attempt which considers fuzzy weighted association rule-based data mining approaches to the facility layout problem. An illustrative example is presented to demonstrate the usefulness of the proposed approaches.

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  AtıfScopus24·OpenAlex16

  İncele