Gülbahar, İbrahim Tümay

Profile Picture
Profile URL
https://hdl.handle.net/20.500.12573/2671
Name Variants
Gulbahar, Ibrahim Tumay
Gulbahar, Ibrahim Tümay
Gülbahar, İbrahim
Job Title
Arş. Gör.
Email Address
ibrahim.gulbahar@agu.edu.tr
Main Affiliation
02.02. Endüstri Mühendisliği
Status
Current Staff
Website
ORCID ID
0000-0001-9192-0782
Scopus Author ID
57202958395
Turkish CoHE Profile ID
340980
Google Scholar ID
d4AOcFIAAAAJ
WoS Researcher ID
GLN-7653-2022
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5415_ibrahim_tumay_gulbahar.jpeg (11.25 KB)

Sustainable Development Goals

7

AFFORDABLE AND CLEAN ENERGY
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3

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11

SUSTAINABLE CITIES AND COMMUNITIES
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1

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3

Citations

13

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2

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Scholarly Output

6

Articles

4

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390/416

Supervised MSc Theses

1

Supervised PhD Theses

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WoS Citation Count

10

Scopus Citation Count

13

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1

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1

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0

WoS Citations per Publication

1.67

Scopus Citations per Publication

2.17

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5

Supervised Theses

1

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AIP Conference Proceedings1
Bitlis Eren Üniversitesi Fen Bilimleri Dergisi1
Mühendislik Bilimleri ve Tasarım Dergisi1
Sakarya University Journal of Science1
Sustainability1
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Now showing 1 - 6 of 6
  • Thumbnail Image
    Article
    Citation - WoS: 10
    Citation - Scopus: 12
    Optimizing Electric Vehicle Charging Station Location on Highways: A Decision Model for Meeting Intercity Travel Demand
    (MDPI, 2023) Gulbahar, Ibrahim Tumay; Sutcu, Muhammed; Almomany, Abedalmuhdi; Ibrahim, Babul Salam K. S. M. Kader
    Electric vehicles have emerged as one of the top environmentally friendly alternatives to traditional internal combustion engine vehicles. The development of a comprehensive charging infrastructure, particularly determining the optimal locations for charging stations, is essential for the widespread adoption of electric vehicles. Most research on this subject focuses on popular areas such as city centers, shopping centers, and airports. With numerous charging stations available, these locations typically satisfy daily charging needs in routine life. However, the availability of charging stations for intercity travel, particularly on highways, remains insufficient. In this study, a decision model has been proposed to determine the optimal placement of electric vehicle charging stations along highways. To ensure a practical approach to the location of charging stations, the projected number of electric vehicles in Turkiye over the next few years is estimated by using a novel approach and the outcomes are used as crucial input in the facility location model. An optimization technique is employed to identify the ideal locations for charging stations on national highways to meet customer demand. The proposed model selects the most appropriate locations for charging stations and the required number of chargers to be installed, ensuring that electric vehicle drivers on highways do not encounter charging problems.
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    Article
    Citation - Scopus: 1
    Electricity Load Forecasting Using Deep Learning and Novel Hybrid Models
    (Sakarya University, 2022) Sutcu, Muhammed; Şahi̇n, Kübra Nur; Koloğlu, Yunus; Çelikel, Mevlüt Emirhan; Gulbahar, Ibrahim Tümay
    Load forecasting is an essential task which is executed by electricity retail companies. By predicting the demand accurately, companies can prevent waste of resources and blackouts. Load forecasting directly affect the financial of the company and the stability of the Turkish Electricity Market. This study is conducted with an electricity retail company, and main focus of the study is to build accurate models for load. Datasets with novel features are preprocessed, then deep learning models are built in order to achieve high accuracy for these problems. Furthermore, a novel method for solving regression problems with classification approach (discretization) is developed for this study. In order to obtain more robust model, an ensemble model is developed and the success of individual models are evaluated in comparison to each other. © 2025 Elsevier B.V., All rights reserved.
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    Article
    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.
  • Thumbnail Image
    Article
    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.
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    Master Thesis
    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.
  • Thumbnail Image
    Conference Object
    Statistical Approach for Table Tennis Athletes' Success
    (Amer Inst Physics, 2018) Goren, Selcuk; Gulbahar, Ibrahim Tumay; Pinar, Muhammed Safak
    This report summarizes the statistical modeling and analysis results associated with the athletes' success and athletes' features. Main purpose of this report is to find any relation between athletes' success and their features. As a tool of creating correlation regression is used with SPSS.