Bu çalışmada, RapidMiner veri madenciliği yazılımı kullanılarak Yapay Sinir Ağları ile altın, gümüş, platin ve paladyum gibi kıymetli madenlerin fiyatlarının tahmin edilmesi gerçekleştirilmiştir. Yapay sinir ağlarını değerlendirmek için beş performans ölçütü; ortalama karesel hata, mutlak hata, göreceli hata, Spearman Rho ve Kendall Tau kullanılmıştır. Bu çalışma, 4 Ocak 2010 ile 14 Aralık 2015 tarihleri arasındaki altın, gümüş, platin, paladyum, Brent Petrol, doğal gaz, 30 yıllık bono, 10 yıllık bono, 5 yıllık bono, S&P 500, Nasdaq, Dow Jones, FTSE100, DAX, CAC40, SMI, NIKKEI, HANH, SEND ve Avro/Dolar rakamlarını içeren veriler üzerine odaklanmıştır. 2015 yılının son çeyreğindeki veriler tahmin ve doğrulama için kullanılmıştır. Sonuçlar, pazar tahminleri için hata oranlarının kabul edilebilir olduğunu göstermiştir.

Bu çalışmanın amacı Korku Endeksi (VIX) ile BIST 100 arasındaki nedensellik ilişkisini tespit etmektir. Çalışmada 03.01.2000 - 09.02.2018 zaman aralığındaki günlük verilerin kullanılarak, VIX ile BIST 100 arasındaki nedensellik ilişkisi frekans alanı nedensellik testi yardımıyla incelenmiştir. Analiz sonuçlarına göre, BİST 100 endeksinden, VIX endeksine doğru ne geçici ne de kalıcı bir nedensellik ilişkisi bulunamamıştır. Bununla birlikte, VIX endeksinden, BİST 100 endeksine doğru hem geçici hem de kalıcı nedensellik ilişkisi tek yönlü olarak tespit edilmiştir. Sonuç olarak, yatırımcılar, BIST100 endeksi için hem kısa hem de uzun dönemde öngörüde bulunurken, VIX endeksinden faydalanabilecektir.

Two critical factors of economic growth are stock exchange and interest rate. This paper investigates the long run relationship between stock market capitalization rate and interest rates in Turkey over the period 1998-2012. Prior to conducting the analysis in a time series, in order to test the stability of the series, a unit root test was initially applied. It is determined that both stock market capitalization rate and interest rate series are not stationary. Long-run relationship is tested by Johansen Co-integration tests. According to the results of the study, there is long-run relationship between stock market capitalization rate and interest rates

The present study evaluated the diagnostic accuracy of immune system algorithms with the aim of classifying the primary types of headache that are not related to any organic etiology. They are divided into four types: migraine, tension, cluster, and other primary headaches. After we took this main objective into consideration, three different neurologists were required to fill in the medical records of 850 patients into our web-based expert system hosted on our project web site. In the evaluation process, Artificial Immune Systems (AIS) were used as the classification algorithms. The AIS are classification algorithms that are inspired by the biological immune system mechanism that involves significant and distinct capabilities. These algorithms simulate the specialties of the immune system such as discrimination, learning, and the memorizing process in order to be used for classification, optimization, or pattern recognition. According to the results, the accuracy level of the classifier used in this study reached a success continuum ranging from 95% to 99%, except for the inconvenient one that yielded 71% accuracy.

Process mining is a new era in the science of data mining and is a subset of business intelligence. Process mining analysis provides an idea about a general process by comparing each process with others in the terms of time and responsible people who deal with the process. For this reason, event logs are checked. Event logs consist of large data. Because the event logs keep all the records that occur during short time intervals. Special programs are needed to examine such data. These programs generate a process map using information such as event ID, activity, time and responsible person. Through the analysis, processes are discovered, monitored and improved. In this study, the tools named ProM, Disco, Celonis and My-Invenio used in process mining were examined and their performance according to usage features compared. According to the obtained results, the usefulness, performance and reporting features of the software used in a process analysis are revealed.