استفاده از الگوریتم CART در پیش‌بینی نوسانات سطح آب زیرزمینی در داخل و خارج از محدوده شبکه آبیاری (مطالعه موردی: منطقه تحت آبیاری شهرستان قزوین)

AbbasNezhad, A and Shahidasht, A. (2013). Vulnerability of Sirjan Plain Due to Aquifer Over Abstraction. Journal of Geography and Urban Planning – Regional 3(7), 85-96. (In Farsi)

Barikani, A., Ahmadian, M. and  Khalilian, S. (2011). Optimal Sustainable Use of groundwater resources in agriculture: Case Study Subsector in Qazvin Plain. Journal of Agricultural Economics and Development 25(2), 253-262. (In Farsi)

Chattamvelli, R. (2011). Data Mining Algorithms, (1th ed.). Oxford: Alpha Science, PP: 274-290.

Corona, O. L., Fuentes, O. E., Casique, E.M., Longoria, P.P. and Moran, T. G. (2016). Data Mining of Historic Hydrogeological and Socioeconomic Data Bases of the Toluca Valley, Mexico. Journal of Water Resource and Protection, 8(4), 522-533.

Gupta, G.K. (2011) Introduction to Data Mining with Case Studies, (2th ed.), Prentice hall of India.

Huajie, D., Zhengdong, D. and Feifan, Deng. (2016). Classification of groundwater potential in chaoyang area based on quest algorithm. College of Defense Engineering, advancing the understanding of our living planet, Beijing, China, 19: 890-893.

Jang, C.S., Chen., S.K. and Ku, Y.M. (2013). Applying indicator-based geostatistical approaches to determine potential zones of groundwater recharge based on borehole data. Catena, 101, 178–187.

Khan, S., Gabriel, H. F. and Rana, T. (2008). Standard precipitation index to track drought and assess impact of rainfall on watertables in Irrigation and Drainage Systems, 22, 159–177.

Kolli, K. and R, Seshadri. (2013). Ground Water Quality Assessment using Data Mining Techniques. International Journal of Computer Applications, 76(15): 39-45.

Kotsiantis, S., Kostoulas, A., Lykoudis S., Argirio, A. and Menagias, K. (2008). Using data mining techniques for estimating minimum, maximum and average daily temperature value. IJMPES. 1(2): 117-121.

Mohammadi, M., Mohammadi Ghaleney, M. , Ebrahimi, K. (2011). Spatial and Temporal Variations of Groundwater Quality of Qazvin plain, Water Research Iran, 5(8), 41-51. (In Farsi)

Naghibi, S. A., Pourghasemi, H. R. and Dixon, B. (2016). GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran. Environmental Monitoring and Assessment, 188(1):44

Oorkavalan, G., Chidambaram, S. M., Mariappan, V., Kandaswamy, G. and Natarajan. S. (2016). Cluster Analysis to Assess Groundwater Quality in Erode District, Tamil Nadu, India. Circuits and Systems, Computer Science & Communications, 7(6): 877-890

Sotoodehnia, A. Sotoodehnia, S. (2016).The Assessment of the role of Taleghan reservoir dam construction on sedimentation in Ghazvin plain irrigation network,14-15 Dec., Faculty of Engineering and Technology, Imam Khomeini International University, Ghazvin, Iran, pp.1-9. (In Farsi)

Stumpp, C., J. Zurek, A.J., Wachniew, P., Gargini, Gemitzi, A., Filippini, M. and Witczak, S. (2016). A decision tree tool supporting the assessment of groundwater vulnerability. Environmental Earth Sciences, 75(1057), 1-7.

Zhao, Y., Li, Lifen., Y and Zhang, L. and Wang, Q. (2016). Groundwater level prediction of landslide based on classification and regression tree. geodesy and geodynamics, l7(5), 348-355.