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Book Part Citation - Scopus: 3Adaptive Intelligent Learning System for Online Learning Environments(World Scientific Publishing Co., 2013) Serçe,F.C.; Alpaslan,F.N.; Jain,L.C.The present chapter deals with an Adaptive Intelligent Learning System (AILS) which is designed to be used withany Learning Management System (LMS). The adaptiveness provides unique method of identifying and monitoring the learner’s learning processes according to their respectivelearning ability. AILS is a multi-agent system. This was developed in the form of JADE agents. The chapter presents the learning model, the system components, agent behavior in learner scenarios, the ontologies used in agent communications, and adaptive strategies. A sample application of AILS toa dummy LMS is also presented. © 2013 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.Book Part Determining Harmonic Fluctuations in Food Inflation(World Scientific Publishing Co., 2022) Akdi,Y.; Ünlü,K.D.; Baş,C.; Karamanoğlu,Y.E.In this study, we start with a brief expression of consumer price index of Turkey. In the next step, we give the theoretical essentials of periodogram-based unit root and harmonic regression model. Periodogram-based unit root test is used to identify both the stationarity of data and periodicities. Periodicity is beyond seasonality; it is the hidden cycles in the data. Thus, it is harder to detect them compared to seasonal cycles. Harmonic-regression-type trigonometric regression models are useful in modeling data which have hidden periodicity. Afterward, the stationarity properties of monthly inflation and monthly food inflation of Turkey for the period between 2004 and 2020 are investigated. Standard augmented Dickey-Fuller unit root test shows that both series are integrated of order one. However, the periodogram-based unit root test shows that monthly inflation has unit root but monthly food inflation does not. After examining the unit root, the hidden cycles in the food inflation are revealed. The cycles in food inflation are important because they may trigger a headline inflation. The main contribution of this study is the identification of the hidden cycles in food inflation. It has cycles of approximately two, four, six and eight years. These cycles, in short, correspond to cycles of two years of consecutive periods. © 2022 by World Scientific Publishing Europe Ltd.Book Part Forecasting the Bist 100 Index With Support Vector Machines(World Scientific Publishing Co., 2022) Ünlü,K.D.; Potas,N.; Ylmaz,M.Recent literature shows that statistical learning algorithms are powerful for forecasting financial time series. In this study, we model and forecast the Borsa Istanbul 100 Index by employing the machine learning algorithm, support vector machine. The dataset contains the highest price, lowest price, closing price and volume of the index for the period between July 2020 and June 2021.We utilize three different kernels. The empirical findings show that linear kernel gives the best result with coefficient of determination of 0.91 and root mean square error of 0.0062. The second best is polynomial kernel, and it is followed by radial basis kernel. The study shows that statistical learning algorithms can be thought of as an alternative to classical time series methodology in forecasting financial time series. © 2022 by World Scientific Publishing Europe Ltd.Book Part Recent Trends on Ulam–Hyers Stability Results of Fixed Point Problems(World Scientific Publishing Co., 2025) Cvetković, M.; Karapınar, E.; Ye Silkaya, S.S.Fixed point theorems have been extensively used in recent years to prove the Ulam–Hyers stability results of functional equations. In this chapter, we collect novel Ulam–Hyers stability results obtained by using well-known fixed point theorems in the setting of a complete metric space. We focus on several types of functional equations and inclusions along with some applications on the stability of the specific integral and differential equation. © 2026 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.
