özkan ünsal | Suleyman Demirel University (original) (raw)

Papers by özkan ünsal

Kaldiracli doviz alim-satim piyasasi, yaygin olarak bilinen ismiyle Forex veya FX, gunluk 5,5 tri... more Kaldiracli doviz alim-satim piyasasi, yaygin olarak bilinen ismiyle Forex veya FX, gunluk 5,5 trilyon dolarlik islem hacmiyle dunyanin en buyuk para piyasasidir. Forex piyasalarinda fiyat yonunun tahmini ve isleme girme yontemleri gelisen teknolojiye paralel olarak her gecen gun degismekte ve gecmis veriler ile egitilerek karar verebilen robotlarin bu alanda etkisi giderek artmaktadir. Makine ogrenmesi, bilgisayarlarin gecmis bilgilerden elde edilen tecrubelerden yararlanarak, gelecekteki olaylari tahmin etmesine ve modelleme yapmasina imkân veren bir yapay zekâ alanidir. Bu calismada, bir makine ogrenme teknigi olan “Naive Bayes“ algoritmasi kullanilarak, gecmisteki veriler isiginda guncel duruma uygun AL ya da SAT sinyali ureten ve bu yonde otomatik islem acan bir robot gelistirilmistir. Robot EUR/USD, GBP/USD, USD/JPY, USD/CHF, USD/CAD, GBP/JPY ve AUD/USD paritelerine ait gecmis veriler uzerine uygulanmis ve elde edilen sonuclar yorumlandiginda Forex piyasalari icin uretilen siny...

Vehicle routing problems (VRP) are complicated problems, which can be encountered in a variety of... more Vehicle routing problems (VRP) are complicated problems, which can be encountered in a variety of different fields and are not possible to solve using conventional methods. Thanks to the technological advancements in areas such as the global positioning system (GPS), geographical information systems (GIS), mobile communication networks, and traffic sensors, it is now possible to solve the VRP in a dynamic and real-time manner. In this study, the school bus routing problem (SBRP), which is a sub-branch of VRPs, was optimized by means of an application developed using Genetic Algorithms(GA), which is one of the heuristic methods. By using the application developed based on mobile communication and GPS, the instantaneous locations of stops and the school bus were determined and the shortest and most convenient route for the vehicle to follow was dynamically identified. The experimental results obtained at the end of this study showed that the existing school bus routes can be optimized...

International Journal of Bio-Inspired Computation, 2018

The vehicle routing problem (VRP) is an optimisation issue that has been studied for more than 50... more The vehicle routing problem (VRP) is an optimisation issue that has been studied for more than 50 years with its numerous subfields. The optimisation of VRP over distribution and transportation systems leads to significant gains in cost and time. There are many metaheuristic methods developed for the solution of the problem; and it was observed that metaheuristic methods prove to produce more successful results compared to common heuristic methods. In this study, a mobile-supported visual application was developed using ant colony optimisation (ACO) and genetic algorithm (GA), which are among the metaheuristic methods for the dynamic school bus routing problem (DSBRP), one of the sub-problems of VRP. The ACO and GA methods were utilised via the application for bus routes of a school located in the province of Ankara and the performance of these methods were compared through the obtained results. It was observed that time and distance values of the routes of current school bus routes may be improved by these two methods.

Mühendislik Bilimleri ve Tasarım Dergisi, Journal of Engineering Sciences and Design, 2018

Araç Rotalama Problemi (ARP) klasik yöntemler ile çözülmesi mümkün olmayan ve birçok alt dalı ola... more Araç Rotalama Problemi (ARP) klasik yöntemler ile çözülmesi mümkün olmayan ve birçok alt dalı olan karmaşık bir problemdir. Bu çalışmada, ARP'nin bir alt dalı olan Okul Servisi Rotalama Probleminin (OSRP) optimizasyonu amaçlanmıştır. ARP ve OSRP incelenmiş, problemler ve geliştirilen çözüm yöntemleri ile ilgili literatüre yer verilmiştir. OSRP'nin optimizasyonu için kümeleme teknikleri ve yapay zeka yöntemleri kullanılarak, GPS, GIS araçları ve mobil uygulama desteği ile bir yazılım geliştirilmiştir. Geliştirilen yazılım Ankara ilinde hizmet veren servis firmalarından toplanan rota verileri üzerinde uygulanmıştır. Elde edilen deneysel sonuçlar, geliştirilen yöntemin, mesafe, zaman ve rakım değişimi parametreleri açısından rotaları başarılı bir şekilde iyileştirilebileceğini göstermiştir.

Vehicle routing problems (VRP) are complicated problems, which can be
encountered in a variety of different fields and are not possible to solve using classical methods. In this study, optimization of the School Bus Routing Problem(SBRP), which is a sub-branch of VRP, is aimed. VRP and SBRP have been studied, and the literature on the problems and developed solution methods have been given. For the optimization of SBRP, by using the clustering and artificial intelligence techniques a software has been developed with the support of the GPS,
GIS tools and mobile application. The developed software has been applied on the route data collected from school service companies which are in the province of Ankara. The obtained experimental results have showed that the developed method can successfully optimize the school bus routes in terms of distance, time and altitude change parameters.

BRAIN. Broad Research in Artificial Intelligence and Neuroscience ISSN 2067-3957, 2018

Proceedings of the 11th International Confenference on Practice and Theory of Automated Timetabling (PATAT-2016), 2016

IAJIT, 2016

Transportation and distribution systems are improving with an increasing pace with the help of cu... more Transportation and distribution systems are improving with an increasing pace with the help of current technological facilities and additionally, the complexity of those systems are increasing. Vehicle routing problems are difficult to solve with conventional techniques. Improving routes used in distribution systems provides significant savings in terms of time and costs. In this paper, current routes in school buses, which is a sub-branch of vehicle routing problems, are optimized using the Ant Colony Optimization (ACO), which is a heuristic artificial intelligence algorithm. Developed software is used for recommending the most suitable and the shortest route illustrated on a map by taking the instantaneous student wait locations online. Results of this study suggest that the current routes can be improved by using the ACO.

The Ninth International Conference on Machine Learning and Applications (ICMLA 2010), 2010

The importance of vocational and technical training is growing day by day in parallel to the deve... more The importance of vocational and technical training is growing day by day in parallel to the developing technology. It is inevitable to utilise opportunities presented by information and communication technologies in order to determine vocational fields in vocational and technical training in the most efficient manner. In this respect, it is possible to create a more efficient tool compared to the current methods by utilising machine learning which is an artificial intelligence model in energy applications that predicts events in the future depending on the past experiences. In the current study, a software is developed that ensures that the system learns about the successful and unsuccessful choices made in the past by applying “Naive Bayes” algorithm, which is a machine learning algorithm, to the data collected concerning the individuals who turned out to be successful or unsuccessful in the vocational technical training process in energy applications. In the software developed, it is aimed that the system recommends the most suitable vocational field for the individual by according to the data collected from the individual who is in the occupation selection process in field energy applications.

10th International Conference on Machine Learning and Applications and Workshops (ICMLA 2011), 2011

Recent developments in information systems as well as computerization of business processes by or... more Recent developments in information systems as well as computerization of business processes by organizations have led to a faster, easier and more accurate data analysis. Data mining and machine learning techniques have been used increasingly in the analysis of data in various fields ranging from medicine to finance, education and energy applications. Machine learning techniques make it possible to deduct meaningful further information from those data processed by data mining. Such meaningful and significant information helps organizations to establish their future policies on a sounder basis, and to gain major advantages in terms of time and cost. This study applies classification algorithms used in data mining and machine learning techniques on those data obtained from individuals during the vocational guidance process, and tries to determine the most appropriate algorithm.

International Journal of Bio-Inspired Computation, 2018

Mühendislik Bilimleri ve Tasarım Dergisi, Journal of Engineering Sciences and Design, 2018

BRAIN. Broad Research in Artificial Intelligence and Neuroscience ISSN 2067-3957, 2018

Proceedings of the 11th International Confenference on Practice and Theory of Automated Timetabling (PATAT-2016), 2016

IAJIT, 2016

The Ninth International Conference on Machine Learning and Applications (ICMLA 2010), 2010

10th International Conference on Machine Learning and Applications and Workshops (ICMLA 2011), 2011