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DURAĞAN ZAMAN SERİLERİNDE UYGUN ARMA MODELİNİN GENETİK ALGORİTMALAR İLE BULUNMASI VE İMKB VERİLERİ ÜZERİNE BİR UYGULAMA

Journal Name:

  • İstanbul Üniversitesi İktisat Fakültesi Mecmuası

Publication Year:

  • 2007

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
Genetic algorithms that mimic the genetics and the principles of natural selection can be applied for the optimization processes and for the computationally intensive problems. In this paper we show that the genetic algorithms can be used to select the best ARMA model. It would be expected that the result of the proposed method can be similar to that of the process of all-possible-regressions which inherently requires too much computation time.
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Abstract (Original Language): 
Genetik ve doğal, seçilim ilkesini büyük ölçüde taklit eden genetik algoritmalar, aptimizasyon süreçlerinde ve hesaplama yükünün çok fazla olduğu durumlarda başarıyla uygulanma potansiyeline sahiptir. Bu çalışmada uygun ARMA modelinin seçiminde ancak tüm mümkün regresyonlartn taratılınastyla elde edilebilecek sonuçlara yakm bir sonucun genetik algoritmalar ile bulunması olanakları sunulmuştur. Yöntemi uygulamak için Eviews 5.0 'da bir program yazılmış ve İMKB endeks verilerine uygulanmıştır.
FULL TEXT (PDF): 
PDF icon arastirmax-duragan-zaman-serilerinde-uygun-arma-modelinin-genetik-algoritmalar-ile-bulunmasi-imkb-verileri-uzerine-bir-uygulama.pdf
  • 1
21-38
  • Turkish

REFERENCES

References: 

Back, T., Fogcl, D.B., Michalewiez, Z. (2000): Evolutionary Computation 2 - Advanced algorithms and Operators, Institute of Physics Publishing, Bristol and Philadelphia.
Balcombe, K.G. (2005): "Model Selection Using Information Criteria and Genetic Algorithms", Computational Economics, 25, p. 207-228.
Dawid, H. (1999): Adaptive Learning by Genetic Algorithms - Analytical Results and Applications to Economic Models, Springer, New York.
Hashemİnia, H., Niaki, S.T.A. (2006): "A genetic algorithm approach to find the best regression/econometric model among the candidates", Applied Mathematics and Computation, 183, p. 337-349.
Haupt, R.L., Haupt, S.E. (2004): Practical Genetic Algorithms, Second Edition, John Wiley & Sons Inc., Canada.
Holland, J.H. (1975): Adaptation İn Natural and Artificial Systems, University of Michigan Press. (Second Edition: MIT Press, 1992).
Mitchell, M. (1999), An Introduction to Genetic Algorithms, MIT Press. 1999. England.
Ong, C.S., Huang, J.İ., Tzeng, G.H. (2005): "Model identification oF ARIMA family using genetic algorithms", Applied Mathematics and Computation, 164, p. 885-912.

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