Arbogast, J. & Franklin, M., 1999- Artificial Neural Networks and high speed resitivity modeling software speed reservoir characterization, Petroleum Engineering International, 75, 2.
Beane, R. E. & Bodnar, R. J., 1995- Hydrothermal fluids and hydrothermal alteration in porphyry copper deposits. In: Wahl, P.W., Bolm, J.G. (Eds.), Porphyry Copper Deposits of the American Cordillera, Tucson, Arizona, Arizona Geological Society, Arizona, pp. 83–93.
Beane, R. E. & Titley, S. R., 1981- Porphyry copper deposits, alteration and mineralization, part II. Economic Geology 75, 235–269.
Benediksson, H., Swain, P. H. & Y Ersoy, O. K.,1990- Neural network approach versus statistical method in classification of multisource remote sensing data. IEEE Transaction on Geoscience and remote sensing, 28, 540-551.
Burnham, C. W., 1979- Magmas and hydrothermal fluids: in Geochemistry of Hydrothermal ore deposits, H. L. Barnes, Jon Wiley & sons, Inc., p. 71- 136.
Calagari, A. A., 2004- Fluid inclusion studies in quartz veinlets in the porphyry copper deposit at Sungun, East-Azarbaidjan, Iran, Journal of Asian Earth Sciences 23, p. 179–189.
Emami, M. H., Babakhani, A. R., 1991- Studies of geology, petrology, and litho-geochemistry of Sungun Cu–Mo deposit, Iranian Ministry of Mines and Metals, p. 61.
Etminan, H., 1977- The discovery of porphyry copper–molybdenum mineralization adjacent to Sungun village in the northwest of Ahar and a proposed program for its detailed exploration. Confidential Report, Geological Report, Geological Survey of Iran, p. 26.
Guo, J. J., Luh, P. B., 2003- Selecting Input Factors for Clusters of Gaussian Radial Basis Function Networks to Improve Market Clearing Price Prediction, IEEE Trans. On Power systems Part B: Cybernetics, Vol. 18, No. 2, pp. 665-672.
Hezarkhani, A., 2006- petrology of intrusive rocks within the Sungun Porphyry Copper Deposit, Azarbaijan, Iran, Asian Earth Science’ p.p. 329-330.
Hezarkhani, A., Williams-Jones, A. E. & Gammons, C. H., 1999- Factors controlling copper solubility and chalcopyrite deposition in the Sungun porphyry copper deposit, Iran. Mineralium deposita, vol. 34, pp. 770-783.
Hezarkhani, A., Williams-Jones, A. E., 1998- Controls of alteration and mineralization in the Sungun porphyry copper deposit, Iran: Evidence from Fluid Inclusion and Stable Isotopes. Economic Geology, Vol. 93, pp. 651-670.
Ke, J., 2002- Neural network modeling of placer ore grade spatial variability: Unpublished Doctoral Dissertation, University of Alaska Fairbanks, 251 p.
Karayiannis, N. B., Weiqun, M. G., 1997- Growing Radial Basis Neural Networks: Merging Supervised and Unsupervised Learning with Network Growth Techniques IEEE Trans. on Neural Networks, Vol. 8, No. 6, pp. 1492-1506.
Koike, K., Matsuda, S., Suzuki, T. & Ohmi, M., 2002- Neural network-based estimation of principal metal contents in the Hokuroku district, Northern Japan, for exploring Kuroko-type deposits: Nat. Resour. Res., v. 11, no. 2, p. 135–156.
Leszek, R., 2004-Adaptive Probabilistic Neural Networks for pattern Classification in Time-Varying Environment, IEEE RANSACTIONS ON EURAL NETWORKS, VOL. 15, NO.4, pp. 11-827.
Menhaj, M. B., artificial intelligent, 1379- Amirkabir university of technology publication, Tehran, first edition.
Wu, X. & Zhou, Y., 1993- Reserve estimation using neural network techniques: Comput. Geosci., v. 9, no. 4, p. 567–575.
Asghari, O. & Hezarkhani, A., 2008- The comparison between the alteration zones in the Sungun porphyry copper deposit (based on the Fluid inclusion investigations), Acta Geologica Hungarica. (in press).
Yama, B. R. & Lineberry, G. T., 1999- Artificial neural network application for a predictive task in Mining: Mining Eng., v. 51, no. 2, p. 59–64, .
Yiu, K. K., Mak, M. W. & Li, C. K., 1999-Gaussian mixture models and robabilistic decision-based neural network for pattern classification: A omparative Study”, Neural Computing and Applications 8(3): pp. 235- 45.