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Information Journal Paper

Title

Comprison of Fuzzy Possibilistic Regression and Fuzzy Least Square Regression Models to Estimate Groundwater Level of Neyshabour Aquifer

Pages

  131-143

Abstract

Groundwater has always been considered as one of the main sources of drinking, agriculture, and industrial water, especially in arid and semi-arid regions. Investigating Groundwater level changes in any region has an important role in planning sustainable water resources management. Continuous decline of Groundwater level has been observed worldwide in the past half-century. Groundwater is the most important and the only source of freshwater in Neyshabour plain. Unallowable discharges of the Groundwater resources and the reduction of recharge factors have caused about 200 million cubic meters deficit in Neyshabour aquifer. Therefore, estimating Groundwater is vitally important for the management of water resources.

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  • Cite

    APA: Copy

    Zeraati Neyshabouri, S., POURREZA BILONDI, M., Kashei Siuki, a., & SHAHIDI, A.. (2020). Comprison of Fuzzy Possibilistic Regression and Fuzzy Least Square Regression Models to Estimate Groundwater Level of Neyshabour Aquifer. IRRIGATION SCIENCES AND ENGINEERING (JISE) (SCIENTIFIC JOURNAL OF AGRICULTURE), 43(1 ), 131-143. SID. https://sid.ir/paper/374863/en

    Vancouver: Copy

    Zeraati Neyshabouri S., POURREZA BILONDI M., Kashei Siuki a., SHAHIDI A.. Comprison of Fuzzy Possibilistic Regression and Fuzzy Least Square Regression Models to Estimate Groundwater Level of Neyshabour Aquifer. IRRIGATION SCIENCES AND ENGINEERING (JISE) (SCIENTIFIC JOURNAL OF AGRICULTURE)[Internet]. 2020;43(1 ):131-143. Available from: https://sid.ir/paper/374863/en

    IEEE: Copy

    S. Zeraati Neyshabouri, M. POURREZA BILONDI, a. Kashei Siuki, and A. SHAHIDI, “Comprison of Fuzzy Possibilistic Regression and Fuzzy Least Square Regression Models to Estimate Groundwater Level of Neyshabour Aquifer,” IRRIGATION SCIENCES AND ENGINEERING (JISE) (SCIENTIFIC JOURNAL OF AGRICULTURE), vol. 43, no. 1 , pp. 131–143, 2020, [Online]. Available: https://sid.ir/paper/374863/en

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