Browsing by Author "Gülbahar, İbrahim Tümay"

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A New Rational Classification Approach by the New Mixed Data Binarization Method
(2023) Gülbahar, İbrahim Tümay; Goktan, Rasim Mete
Sınıflandırma algoritması, yeni gözlemlerin kategorisini belirlemek için kullanılan denetimli bir öğrenme tekniğidir. Ancak bazı durumlarda nicel ve nitel verilerin birlikte kullanılması gerekir. Bu yaklaşımla nicel ve nitel verilerin birlikte kullanılmasında karşılaşılan sorunlar aşılmaya çalışılmıştır. Bu çalışmada, gerçek dünyada veriler ikili, sayısal veya kategorik gibi farklı türlerde sınıflandırıldığından, tüm veri türlerini ikili verilere dönüştürerek yeni bir sınıflandırma tekniği modellenmektedir. Bu sayede çok özellikli veri sınıflandırma problemleri için daha doğru ve verimli bir karma veri ikilileştirme yaklaşımı geliştirilmiştir. Öncelikle mevcut veri setinden sınıfları belirlenmektedir ve ardından yeni önerilen veri ikilileştirme yaklaşımını kullanarak yeni örnekleri bu önceden belirlenmiş sınıflara sınıflandırılmaktadır. Bu algoritmanın her adımının nasıl verimli bir şekilde gerçekleştirilebileceğini sayısal bir örnekle gösterilmiştir. Ardından, önerilen yaklaşımı iyi bilinen bir iris veri kümesine uygulamış ve modelimiz önceki yaklaşımlara göre umut verici sonuçlar ve iyileştirmeler verdiği gösterilmiştir.
Optimal Location Determination of Electric Vehicle Charging Stations: A Case Study on Turkey's Most Preferred Highway
(2022) Gülbahar, İbrahim Tümay; Sütçü, Muhammed
Today, electric vehicles are seen as one of the most suitable and environmentally friendly alternatives to internal combustion engine vehicles. An important issue related to the dissemination of electric vehicles is the location of the vehicle charging network and specifically the optimum location selection of the charging stations. Generally, most of the studies focus on popular destinations such as city centers, shopping areas, bus stations, and airports. Although these places are often used in normal life, they can usually provide an adequate solution for daily charging needs due to the number of alternative charging stations. However, finding adequate charging stations is not possible in intercity travels especially in highways. In this paper, we proposed a decision model to determine the location of electric car charging stations in highways. We create an optimization model to decide the optimum locations for the charging stations that can meet the customer demands on the Istanbul-Ankara highway. The proposed model determines optimum charging stations that enable passengers traveling with their electric vehicles to travel in Istanbul-Ankara highway in the shortest time.
Türkiye'de Elektrikli Araç Sarj İstasyonu Lokasyonu Belirleme
(Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023) Gülbahar, İbrahim Tümay; Sütçü, Muhammed
Electric vehicles are now regarded as one of the best and greenest replacements for internal combustion engine vehicles. For the widespread use of electric vehicles, the construction of the vehicle charging network and, in particular, the choice of the appropriate site for the charging stations, are viewed as critical issues. The majority of studies on the topic concentrate on well-known locations like city centers, shopping malls, and airports. Because there are so many alternative charging stations, even though these and comparable locations are regularly used in everyday life, they can usually provide an appropriate solution to the daily charging need. For intercity travel, it is impossible to find enough charging stations, especially on highways. To choose the position of electric vehicle charging stations on highways, a decision model has been suggested in this study. The anticipated number of electric vehicles in Türkiye over the next few years is projected in order to acquire a realistic approach to the location of charging stations, and this amount is employed as a significant input in the facility positioning model. The best places for charging stations on state highways that can meet customer demand were then identified using an optimization technique. The suggested model selects the most suitable locations for charging stations and the number of chargers that should be installed there while also making sure that drivers of electric vehicles on highways don't run into charging issues.