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Günümüzde, birçok araştırmacı optimizasyon problemleri çözen algoritmaları geliştirme eğilimindedir. Gerçek dünya problemleri ise genelde birden çok amaca sahip oldukları için çok amaçlı optimizasyon problemleri üzerine geliştirilen algoritmalar trend olmuştur…

One of the most well-known and easy-to-design converter of DC-DC converters is DC-DC Boost converter. DC-DC boost converters are widely utilized in industrial applications. Therefore, output voltage regulation of the boost converter is a popular issue that res…

Flexible job shop scheduling problem (FJSSP) contains two sub-problems, that is, routing and scheduling. Each operation is assigned to a machine among a set of alternative machines in the routing sub-problem, whereas the assigned operations on all machines are…

Asenkron motorlar, endüstrideki en yaygın kullanılan motorlardır. Çok avantajlı bir yapıda olduklarından üretim hatlarının her noktasında bulunurlar. Bu motorların arızalarını hızlı ve kolay bir şekilde tespit etmek arzu edilir. Bu makalede, asenkron motorları…

The hub location problem deals with locating hub facilities and allocating non-hub nodes to hub. Hub location problem is classified as p-hub median problem, p-hub center problem, hub covering problem and hub location problem with fixed cost in the literature. …

In the phases of hydrological model calibration, the impact of control parameters of optimization algorithms on the related fitness (cost) function (reaching the global solution correctly and expeditiously) is rather essential. These control parameters’ dynami…

Differential evolution algorithm (DEA) is one featured kind of population based evolutionary algorithms. Although it is stated in previous studies that the algorithm is more sensitive to the crossover rate, it is tried out in this study whether DEA depends on …

Kanser, insan ölümlerine sebep olan hastalıklar arasında ikinci sırada gelmektedir. Günümüzde insanların kansere yakalanma oranları giderek artmaktadır. Kanser; kötü beslenme, sigara ve alkol kullanımı, uzun süre güneş ışığına maruz kalma gibi birçok nedenle o…

Prediction in the medical field is a challenging problem and as a result many researchers have used different artificial intelligent methods including conventional Self Organizing Map (SOM) to achieve this task. SOM is a specialized clustering technique that h…

Deep learning is a machine learning sub-field that uses deep neural networks. Instead of customized algorithms for each study in this field, it is aimed to cover the wider data set of solutions based on learning the data. Deep learning is a promising approach …

In recent years, computer vision has taken great strides in understanding and recognition the visual scenes together with deep learning technologies. Object recognition is one of the key areas of the computer vision applications. It is mainly concerned with re…

We propose using support vector machines (SVMs) as a machine learning classifier in a grain-conditionmonitoring system. This system is used to proactively monitor the silobag-stored grain condition. The system consists of a wireless sensor network (WSN) and a …

Ball and beam system is an experimental set for control system design that the position of the ball on a beam is changed with respect to the reference direction by changing the angle of the beam. The PID controller is applied to this problem. The performance o…

Correct orientation of students during education is very crucial for preventing future failures. Students who cannot graduate at the time may cause negative impacts on the family and the country's economy as well as the decrease of the young labor force. This …

Robot algorithms require faster and more efficient computing due to increasing integration of robot arms to automation systems and expanding capabilities of robotic systems. Inverse kinematics calculations used in trajectory generation is one of these algorith…

Machine learning and artificial intelligence have become an integral part of people's culture, influencing the lives of most people today. Machine learning is a subset of data science that uses statistical models to create insights and predictions. Machines sh…

Traffic flow forecasting has an important place in designing a successful intelligent transportation system. The success of the forecasting is related to the accuracy and timely acquisition of the traffic flow data. The inadequacy in the number of data has led…

The U-shaped assembly line balancing (UALB) problem has been extensively investigated in the existing academic literature. However, only a limited number of studies consider the uncertainty in the assembly lines. In this research, a robust formulation is devel…

One of the fastest 3D data acquisition methods is LiDAR scanning technology. By using LiDAR scanners, 3D point clouds of the scanned seen is obtained easily. Although the scanning phase is fast, the meaningful and effective 3D visualization of the scene requir…

It is well known that non-Gaussian noise deteriorates the detection performances of the conventional detection methods. This problem is also encountered in cognitive radio where impulsive structure of noise negatively affects spectrum sensing. Multistage detec…