Person: Aktaş, Ahmet
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Dr. Öğr. Üyesi
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Aktaş
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Ahmet
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Ahmet AKTAŞ
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Publication Prioritization of Districts in terms of Disaster Preparedness Planning: A Case Study for the Expected Istanbul Earthquake(2022) Ahmet AKTAŞ; Aktaş, Ahmet; Türk Hava Kurumu Üniversitesi, Endüstri Mühendisliği Bölümü, Ankara, TürkiyePreparedness is the second among the four phases of disaster management after mitigation. In big cities with crowded populations like İstanbul, development of a single holistic disaster preparedness plan would be too complex. At this point, the prioritization of districts is needed because of the existence of a limited amount of available resources (time, staff, money, etc.) plan development stage. This decision can be affected by several factors, so this decision can be defined as a multiple criteria decision-making problem. The main aim in this paper is to develop an analytic approach to obtain the priority rank of districts of the city for disaster preparedness plan development. To do so, a hybrid multiple criteria decision-making model based on SWARA (Stepwise Weight Assessment Ratio Analysis) and WASPAS (Weight Aggregated Sum Product Assessment) is proposed. A case study on earthquake preparedness planning in districts of İstanbul is presented to demonstrate the applicability of the proposed model. Obtained results of the model would be helpful for policy making in volunteer organizations, municipality, and government level.Publication Clustering of European Countries in terms of Healthcare Indicators(International Journal of Computational and Experimental Science and Engineering (IJCESEN), 2019-03-31) Billur ECER; Ahmet AKTAŞ; Aktaş, AhmetHealth is always considered as one of the most important issues related to human being. Due to this importance, governments should primarily provide the best healthcare services to their citizens. Some indicators can show the quality of healthcare services in the country. However, one country can have a higher value of one indicator and can have a lower value of another. Thus, countries can be categorized in terms of quality of healthcare services. Clustering is a useful tool for comparing countries and defining the similar countries in terms of healthcare services. In this study, 28 European Union (EU) countries were evaluated on 14 health factors and the number of clusters was determined by the generally accepted rule of thumb. To cluster countries, k-means clustering method is run in WEKA software for two cluster numbers and four different initial solution approaches. The resulting clusters were evaluated according to the Spearman rank correlation coefficient using the order of the GDP per capita values of the countries in each cluster. It seems using four clusters with Canopy initial solution approach is the most appropriate way of clustering.Publication FARKLI UZAKLIK HESAPLAMA YAKLAŞIMLARININ TOPSIS ÜZERİNDE KULLANILABİLİRLİĞİNİN İNCELENMESİ(Journal of the Faculty of Engineering and Architecture of Gazi University, 2017-03-23) Mehmet Kabak; Fatih Sağlam; Ahmet Aktaş; Aktaş, Ahmet