Now showing items 1-9 of 9

  • Feature Extraction Based on Deep Learning for Some Traditional Machine Learning Methods 

    Deep learning is a subfield of machine learning and deep neural architectures can extract high level features automatically without handcraft feature engineering unlike traditional machine learning algorithms. In this paper, we propose a method, which combines feature extraction layers of a convolutional neural network with traditional machine learning algorithms, such as, support vector machine, gradient boosting machines, and random forest. All of the proposed hybrid models and the above mentioned ...

  • Feature selection and discretization for improving classification performance on CAC data set 

    Authors:Sayın, Kamran Emre
    Publisher and Date:(Kadir Has University, 2013)
    Data Mining usage in Health Sector increased much in this decade because of the need for efficient treatment. From cost-cutting in medical expenses to acting as a Decision Support System for patient diagnosis, Data Mining nowadays is a strong companion in Health Sector. The dataset used in this thesis belongs to Dr. Nurhan Seyahi. Dr. Nurhan Seyahi and his colleagues made a research about Coronary Artery Calcification in 178 patients having renal transplantation recently. They used conventional ...

  • Heuristic methods for postoutage voltage magnitude calculations 

    Authors:Ceylan, Oğuzhan; Özdemir, Aydoğan; Dağ, Hasan
    Publisher and Date:(Tübitak, 2016)
    Power systems play a significant role in every aspect of our daily lives. Hence, their continuation without any interruption (or with the least duration of interruption due to faults or scheduled maintenances) is one of the key aims of electrical energy providers. As a result, electrical energy providers need to check in great detail the integrity of their power systems by performing regular contingency studies of the equipment involved. Among others, line and transformer outage simulations ...

  • Konutların Günlük Elektrik Güç Tüketimi Tahmini İçin Uygun Model Seçimi 

    Authors:Çayır, Aykut; Dağ, Hasan
    Publisher and Date:(Fırat Üniv. Fen Bilimleri Enst., 2018)
    Zamana bağlı değişim gösteren olayların modellenmesi zorlu bir veri analizi problemidir. Bu olaylardan biri olan elektrik güç tüketiminde ise veriden mevsimsel etki ve tatil günleri gibi örüntülerin öğrenilerek bir tüketim tahmin modelinin geliştirilebilmesi için klasik makine öğrenmesi ve derin öğrenme yöntemlerinden yararlanılmaktadır. Bu çalışmada, İngiltere’nin Londra şehrindeki belirli bir bölgede 30 farklı eve ait yaklaşık 3 yıllık elektrik güç tüketimi veri kümesi kullanılarak uygun bir ...

  • Machine learning model to predict an adult learner's decision to continue ESOL course 

    Authors:Dahman, Mohammed R.; Dağ, Hasan
    Publisher and Date:(Springer, 2019)
    This study investigated the ability of the demographic and the affective variables to predict the adult learners' decision to continue ESOL courser. 278 adult learners, enrolled on ESOL course at FLS institution in Istanbul, Turkey, participated in the study. The result showed that the continued or dropped out groups, demonstrated statistical differences in the demographic variable (the placement test score) with a magnitude of large effect size (.378). Additionally, the result showed the effect ...

  • .Net yazılım çerçevesi kullanılarak KOBİ'lere özel bütçe sisteminin geliştirilmesi 

    Authors:Cesur, Kazım
    Publisher and Date:(Kadir Has University, 2012)
    Bu tezin amacı piyasada çeşitli yollar ile yapılan bütçe uygulamalarına alternatif olarak modern bir yöntem ile kobilerin bütçe yapmalarına olanak sağlamaktır.Bu yöntem, .NET Framework yazılım çerçevesinde bulunan VB.NET programlama dili ve veri erişimi için ADO.NET objeleri kullanılarak geliştirilmiştir.Piyasada bulunan bütçe yapıları genelde özel kapsamda olup genel bir kitleye hitap etmemekte ve ihtiyacı karşılamamaktadır.Amacımız bu yazılım vasıtasıyla tüm kobilerin kullanabileceği bir bütçe, ...

  • The performance wise comparison of the most widely used noSQL databases 

    Authors:Aladily, Ahmed
    Publisher and Date:(Kadir Has University, 2015)
    This work deals with the comparison of the most widely used noSQL databases. Chapter one deals in great details with the SQL databases and the noSQL databases including characteristics and the four types of noSQL databases, the second Chapter deals with the characteristics of the SQL and noSQL databases and the main differences between SQL databases and the noSQL databases. The third chapter deals with the architecture of the Couchdb, Mongodb, Cassandra, and Hbase. Chapter four deals with installation ...

  • A sparsity-preserving spectral preconditioner for power flow analysis 

    Authors:Yetkin, Emrullah Fatih; Dağ, Hasan
    Publisher and Date:(Tübitak, 2016)
    Due to the ever-increasing demand for more detailed and accurate power system simulations, the dimensions of mathematical models increase. Although the traditional direct linear equation solvers based on LU factorization are robust, they have limited scalability on the parallel platforms. On the other hand, simulations of the power system events need to be performed at a reasonable time to assess the results of the unwanted events and to take the necessary remedial actions. Hence, to obtain ...

  • Website category classification using fine-tuned BERT language model 

    The contents on the Word Wide Web is expanding every second providing web users a rich content. However, this situation may cause web users harm rather than good due to its harmful or misleading information. The harmful contents can contain text, audio, video, or image that can be about violence, adult contents, or any other harmful information. Especially young people may readily be affected with these harmful information psychologically. To prevent youth from these harmful contents, various web ...