The Black Sea coasts of Turkey have important examples of geological heritage with coastal cliffs in terms of geological formations and features. The Güzelcehisar Basalt Columns (GBCs) formation and its coast have been chosen as a research area in this article in terms of its basalt columns, rare coastal geological diversity and coastal geotourism potential. This paper presents the results of a visitor survey undertaken at the GBCs formation and its coast, located in the rural coastal part of Bartın province in the Western Black Sea Region of Turkey. This survey was conducted in 2020 to assess the tourism shoulder season visitors to the Güzelcehisar village. With the survey, its aim was to determine the awareness of the visitors on geoconservation and geodiversity and to evaluate the understanding of geological heritage and geotourism. In addition, it was desired to set visitor expectations to improve the geotourism experience. It was found that visitors had a high level of understanding and awareness of the terms “geodiversity”, “geoheritage”, “geotourism” and “geoconservation”. However, this survey also shows that there is less emphasis on the need to protect the geodiversity in Güzelcehisar. Guided walking is preferred in order to improve visitor understanding and improve experiences. These survey findings contain guiding explanations for studies that could provide a wider interpretation of the perceptions, experiences and expectations of visitors regarding the sustainable development of areas with similar coastal geotourism potential in Turkey.

Type-2 fuzzy sets were initially given by Zadeh as an extension of type-1 fuzzy sets. There is a growing interest in type-2 fuzzy set and its memberships (named secondary memberships) to handle the uncertainty in type-1 fuzzy set and its primary membership values. However, arithmetical operators on type-2 fuzzy sets have computational complexity due to third dimension of these sets. In this study, we present some mathematical operators which can be easily applied to type-2 fuzzy sets and numbers. Also, mathematical functions of type-2 fuzzy numbers are given according to their monotonicity. These functions are adapted to reliability and distribution functions of the random variables with the type-2 fuzzy parameters. These functions are applied to Exponential, Chi-square, Weibull distributions with respect to monotonicity of the parameters of these distributions.

The main objective of this study is to determine the knowledge and awareness levels of climate change among preparatory class students at Zonguldak Bülent Ecevit University in the Western Black Sea Region of Türkiye using an unsupervised clustering approach. Within this scope, a survey was administered to university students (n = 280). Participant scores for the survey sections containing five-point Likert-type questions on climate change awareness were calculated using min–max normalization. The normalized data was then processed using the k-means algorithm, a well-known technique in unsupervised machine learning. This resulted in a classification (clustering) related to climate change awareness. The number of clusters was determined using the Silhouette index. Three clusters identified using k-means and Silhouette index ($S\approx 0.55)$ revealed the knowledge and application levels of student groups regarding climate change awareness. As a result of clustering, it was determined that Cluster-3 students (n = 134, 47.9%), defined as having a high level of knowledge and application, had a higher impact value in their overall assessments of green space-focused issues related to climate change awareness compared to the overall assessments of students in other clusters. Some notable findings concerning the attitudes of Cluster-3 students highlight climate change awareness-related practices. These include minimizing water consumption to levels necessary for ecosystem water management (mean = 95.7, std. deviation = 10.9) and exercising controlled, sustainable daily energy use to alleviate pressure on green spaces (mean = 94.4, std. deviation = 12.5). This study offers practical insights for policymakers, educators, and institutions, emphasizing the need to enhance climate education and to promote the active involvement of younger generations in shaping sustainable environments.

Artan rekabet ortamında varlığını sürdürmek isteyen işletmeler için tedarikçi seçim ve değerlendirmeleri önemli bir yere sahiptir. İşletmeler uygun tedarikçi seçimi ile müşteri beklentilerini en iyi şekilde karşılamayı hedeflemektedir. Bu çalışmada, tedarikçi seçimi ve değerlendirmeleri için sezgisel bulanık kümelere dayalı bütünleşik bir yaklaşım önerilmektedir. Önerilen yaklaşım ile karar verici algı farklılıkları kaynaklı belirsizlikler ait olma ve ait olmama dereceleri ile detaylı şekilde incelenmektedir. Bu yaklaşım, inşaat sektöründe faaliyet gösteren bir işletmenin tedarikçi seçimi ve değerlendirmelerine uygulanmıştır. Uygulamada, ekonomik kriterlere dayalı karar verici öznel değerlendirmeleri ile işletme mevcut değerlendirme puanları birleştirilerek karma veritabanı oluşturulmuştur. Klasik ve bulanık öbekleme yaklaşımları ile tedarikçi firma sıralama ve sınıflandırmaları elde edilmiştir. Karma veritabanı için bulanık öbekleme yapısı %99,1; klasik öbekleme yapısı ise %94,4 doğruluk oranı ile oluşmuştur. Ayrıca, bulanık ve klasik öbekleme sonuçları içerisinde sadece tedarikçi değerlendirme puanlarına ait öbeklemenin, sırasıyla, %90,7 ve %74,1 doğruluk oranına sahip olduğu görülmüştür. Algı farklılıklarının tedarikçi seçimine yönelik karar almadaki etkileri önerilen bütünleşik yaklaşımla açıklanmıştır.