Determining of The Achievement of Students by Using Classical and Modern Optimization Techniques
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Mathematical modelling, fuzzy logic, elementary educationAbstract
The purpose of this study is to investigate effects of sleeping hours and study time on students' achievement and to find at which points the minimum and maximum achievement level occurs. Participants of this study are 8th grade students who are students of a public secondary school in Isparta, Yenisarbademli. 12 students participated in this research. Results of five trial exams that students were used in order to determine achievement levels of students. The data for students sleeping hours and study time emerged from interviews. During the interview, students were asked about that their sleeping hours and study time of in a week period before each exam. Data that emerged from interview were categorized by the researcher. Data were evaluated using MATLAB 7.012. (R2011A). In this study, minimum and maximum points were identified using global optimization methods.
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Ahlawat, N., Gautam, A., & Sharma, N. (2014). Use of Logic Gates to Make Edge Avoider Robot. International Journal of Information & Computation Technology, 4(6), 630.
Altun, S. A. & Çakan, M., (2008). Öğrencilerin Sınav Başarılarına Etki Eden Faktörler: LGS/ÖSS Sınavlarındaki Başarılı İller Örneği. Elementary Education Online, 7(1), 157-173.
Arlinghaus, S. L. (1994). PHB Practical Handbook of Curve Fitting. CRC Press.
Center, B. & Verma, B. P. (1998). Fuzzy Logic for Biological and Agricultural Systems. Artificial Intelligence Review, 12, 213-225.
Chai, Y. , Jia L., & Zhang, Z. (2009). Mamdani Model based Adaptive Neural Fuzzy Inference System and its Application. International Journal of Computational Intelligence, 5(1), 22-29.
Dubois, D. & Prade, H. (1980). Fuzzy Sets and Systems: Theory and Applications. Acedemic Press Inc. p. 144.
Ge R.P. (1987). The theory of filled function method for finding global minimizer of a nonlinearly constrained minimization problem. J. Comput. Math., 5(1), 1-9.
Ge R.P. (1990). A filled function method for finding global minimizer of a function of several variables. Mathematical Programming, 46, 191-204.
Ge R.P. & Qin Y.F. (1987). A class of filled functions for finding global minimizers of a function of several variables. J. Optimiz. Theory. App., 54, 241-252.
Karagoz, S., Zülfikar, H., & Kalaycı, T. (2014). Öğrenme sürecine ilişkin değerlendirmeler ve fuzzy karar verme tekniği ile sürece dair bir uygulama, İstanbul üniversitesi sosyal bilimler dergisi, 2014/1, 56-71.
Keskin, G. & Sezgin B. (2009). Bir Grup Ergende Akademik Basarı Durumuna Etki Eden Etmenlerin Belirlenmesi, Fırat Saglık Hizmetleri Dergisi, 4(109).
Koçoğlu, D., Kesgin, M.T., & Kulakcı, H. (2010). İlköğretim .kademe öğrencilerinin uyku alışkanlıkları ve uyku sorunlarının bazı okul fonksiyonlarına etkisi. Sağlık Bilimleri Fakültesi Hemşirelik Dergisi, 24-32.
Kolb, W. M. (1984). Curve Fitting for Programmable Calculators. Syntec, Incorporated. Liu X., (2001). Finding global minima eith computable filled function. J. Global Optim., 19, 151-161.
Liu, X., (2002). Several filled functions with mitigators. Appl. Math. Comput., 133, 375-387.
Liu, X., (2007). A new approach for solving the multimodal economic load dispatch problem, Proc. of IEEE PES, FL, USA.
Mamdani, E. H. (1974). Application of fuzzy algorithms for control of simple dynamic plant. Proc. IEEE 121(12), 1585-1588.
Mamdani, E. H. & Assilian, S. (1975), An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7(1) ,1-13.
Özcan, G. (2006). İlköğretim dördüncü ve beşinci sınıf öğrencilerinin ders çalışma alışkanlıklarının ve ortamlarının incelenmesi. Marmara Üniversitesi Eğitim Bilimleri Enstitüsü, yayınlanmamış yüksek lisans tezi.
Sakawa, M. (1993). Fuzzy Sets and Interactive Multiobjective Optimization, Plenum Press, New York.
Saltan, M., Saltan, S., & Şahiner, A. (2007). Fuzzy logic modeling of deflection behavior aganist dynamic loading in flexible pavements. Construction and Building Materials 21, 1406-1414.
Sugeno, M. & Takagi, T. (1983). Multi-dimensional Fuzzy Reasoning. Fuzzy Sets and Systems, 9(2).
Şahiner, A. & Gokkaya, H. (2012). An application of filled function method to the hardness property of Fe-Mn Binary Alloys, Uncertainty Modeling in Knowledge Engineering and Decision Making, 10th International FLINS Conference, İstanbul.
Şahiner A., Gokkaya H., & Yiğit T. (2012). A new filled function for nonsmooth global optimization. AIP Conf. Proc., 1479, 972
Şahiner, A. & Yilmaz, N. (2014). On Filled Function Method and Applications. 15th ISEOS Proceeding Book, pp. 864-871.
Şener, K. (2001). İlköğretim öğrencilerinin çalışma alışkanlıklarının matematikteki başarılarına etkisi, Fırat Üniversitesi Sosyal Bilimler Enstitüsü, yayınlanmamış yüksek lisans tezi.
Takagi, T. & Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. IEEE Trans. Syst., Man and Cybernetics 15, 116-132.
Uçar, G. (1997). Birleştirilmiş sınıflar fen bilgisi dersi ışık ünitesinde öğrenci başarısına öğrencilerin çalışma alışkanlıkları ve öğretmenlerin ders işleme yöntemlerinin etkisi. Marmara Üniversitesi Sosyal Bilimler Enstitüsü, yayınlanmamış yüksek lisans tezi.
Wu, Z.Y., Bai, F.S., Lee H.W.J., & Yang Y.J. (2007). A filled function method for constrained global optimization. J. Glob. Opt., 39, 495-507.
Yang, Y. & Shang Y. (2006). A new filled function method for unconstrained global optimization. Applied Mathematics and Computation, 173, 501-512.
Zadeh, L. A. (1965). Fuzzy sets. lnformation and Control, 8, 338-352.
Zadeh, L.A. (1973). Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man and Cybernetics, 3, 28-44.
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning: part 1, Information Sciences, 8(1), 199-249.
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning: part 2, Information Sciences, 8(1), 301-357.
Zadeh, L. A. (1976). The concept of a linguistic variable and its application to approximate reasoning: part 3, Information Sciences, 9(2), 43-80.
Zhang, L-S, Ng, C-K, & Li, D. (2004). Tian W-W, A New Filled Function Method for Global Optimization. Journal of Global Optimization, 28, 17–43.
Zimmermann, H. J. (2010). Fuzzy Set Theory. Wiley Interdisciplinary Reviews: Computational Statistics, 2, 317–332.
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