Abosedra, S. ve Baghetani, H., “On The Predictive Accuracy of Crude Oil Futures Prices”, Energy Policy, Volume:32, 2004.
Aklin, K. ve Atman, S., Küresel Petrol Stratejilerinin Jeopolitik Açıdan Dünya ve Türkiye Üzerindeki Etkileri, İstanbul: İstanbul Ticaret Odası, Yayın-No:2006-48, 2008.
Alexandridis A., Livanis E, "Forecasting Crude Oil Prices Using Wavelet Neural Networks".In the proc. of 5th FSDET, Athens, Greece, 8 May, 2008.
Amin-Naseri, M. R. ve Gharacheh, E. A.,“A hybrid artificial intelligence approach to monthly forecasting oil price time series”. Proceedings of EANN, 2007.
Bernabe, A. ve diğerleri, “A Multi-Model Approach for Describing Crude Oil Price Dynamics”, Physica A, Volume:338, 2004.
Bianchini, M., Frasconi, P. & Gori, M. (1995) Learning without local minima in radial basis function networks. IEEE Trans. Neural Networks 6(3), s.749-755.
Broomhead DS, Lowe D.(1988), “Multivariable functional interpolation and adaptive Networks”, Complex Systems 2: s.321–355.
Chatfıeld C.,(2003),The analysis of time series: an introduction, CRC Pres
Chen, S., Cowan, C. F. N., Grant, P. M. (1991), “Orthogonal least squares learning algorithm for radial basis function networks.”, IEEE Trans. Neural Networks 2(2), s.302-309.
Cybenko G. (1989), “Approximation by superpositions of a sigmoidal function. Mathematical Control Signals Systems” 2: s.303–314.
Fausett, L.(1994), Fundamentals of Neural Networks: Architectures, Algorithms and Applications, Prentice Hall.
Fernandez, V., “Forecasting commodity prices by classification methods: The cases of crude oil andnatural gas spot prices”, Banco Central De Chile Conference, July 27, 2007.
Franses P. H.(1996),Periodicity And Stochastic Trends in Economic Time Series, Oxford University Press
Frechtling D. C.(1996), Practical Tourism Forecasting, Elsevier
Ghaffarı, A. ve Zare, S., “A Novel Algorithm For Prediction Of Crude Oil Price Variation Based On Soft Computing”, Energy Economics, Volume:31, 2009.
Harrald, P. G. ve Kamstra, M., “Evolving Artificial Neural Networks To Combine Financial Forecasts”, IEEE Transactions On Evolutionary Computation, Volume:1, No:1, 1997.
Haykin, S.( 1999),Neural Networks - A Comprehensive Foundation, Prentice Hall.
Hornik K, Stinchcombe M, White H.(1989). “Multilayer feedforward networks are universal approximators.”, Neural Networks 2: s.359–366.
Hornik K. (1991), “Approximation capability of multilayer feedforward networks.” ,Neural Networks 4: s.251–257.
Kaboudan, M. A., “Compumetric Forecasting Of Crude Oil Prices”, Proceedings of The 2001 Congress on Evolutioanry Computation, Volume:1, 2001.
Kulkarni, S. ve Haidar, I., “Forecasting Model For Crude Oil Price Using Artificial Neural Networks And Commodity Futures Prices”, International Journal of Computer Science and Information Security, Volume:2, No:1, 2009.
Kuvulmaz J., Usanmaz S., Engin S. N.(2005), “Time-Series Forecasting by Means of Linear and Nonlinear Models.”, MICAI 2005, s.504-513
Moody, J. & Darken, C. J. (1989), “Fast learning in networks of locally-tunes processing units.” ,Neural Computation 1(2), s.281-294.
Öztemel, E.(2003),Yapay Sinir Ağları, Papatya Yayıncılık, İstanbul.
Pan, H., Haidar, I. ve Kulkarni, S., “Daily Prediction Of Short Term Trends Of Crude Oil Prices Using Neural Networks Exploiting Multimarket Dynamics”, Front. Comput. Sci., Volume:3, No:2, 2009.
Park, J. ve Sandberg,I.W.(1991),” Universal approximations using Radial-Basis-Function Network.”, Neural Computation 3(2), s.246-257
Powell MJD.(1987),”Radial basis functions for multivariable interpolation: a review. In Algorithms for Approximation”, Mason JC, Cox MG (eds.) Carendon Press: Oxford; s.143–167.
Tang, Z, Fishwick, P.A.(1993),”Feedforward neural nets as models for time series forecasting”,ORSA Journal on Computing, Vol. 5 (4), s.374–385.
Uğurlu, E. ve Ünsal, A., “Ham Petrol İthalatı ve Ekonomik Büyüme: Türkiye”, 10. Ekonometri ve İstatistik Sempozyumu‟na sunulan bildiri, Erzurum 27-29 Mayıs 2009.
Xıe, W. ve diğerleri, "A New Method for Crude Oil Price Forecasting Based on Support Vector Machines", Lecture Notes in Computer Science, Volume:3994, 2006.
Zhang, G., Patuwo, B. E. ve Hu, M. Y. (1998) “Forecasting with artificial neural networks: the state of the art”, International Journal of Forecasting, 14, s.35-62.
