مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

1,194
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

FORECASTING SPATIOTEMPORAL WATER LEVELS BY NEURAL KRIGING METHOD IN TABRIZ CITY UNDERGROUND AREA

Pages

  14-24

Abstract

 Groundwater level variations can essentially affect the execution of many engineering projects. Accordingly, due to the projects underway in Tabriz district and especially Tabriz Underground Project (METRO), spatiotemporal prediction of the groundwater level is crucial. Due to the aquifer complexity in the Tabriz area, there are problems in using classical mathematical models. In this research a combination of the ARTIFICIAL NEURAL NETWORKS and GEOSTATISTIC MODELs were applied as a new method for spatiotemporal prediction of groundwater levels using selected piezometers. For this purpose, the different neural networks were examined for groundwater level forecasting in central piezometer and an optimal ANN architecture was identified. This ANN structure was then used for modeling the selected piezometers. The results of these models were used as the inputs of the geostatistics model for forecasting spatial groundwater level in the study area. Two year monthly groundwater level prediction data in selected piezometers resulted by ANN modeling were among these input data. In order to obtain a high efficiency model, different methods of the GEOSTATISTIC MODEL were used. Finally the obtained model was tested by water level data in piezometers other than those used for model calibration. The results of this HYBRID MODEL were acceptable.

Cites

  • No record.
  • References

    Cite

    APA: Copy

    ASGHARI MOGHADDAM, A., NORANI, V., & NADIRI, A.O.. (2009). FORECASTING SPATIOTEMPORAL WATER LEVELS BY NEURAL KRIGING METHOD IN TABRIZ CITY UNDERGROUND AREA. IRAN-WATER RESOURCES RESEARCH, 5(1 (13)), 14-24. SID. https://sid.ir/paper/100360/en

    Vancouver: Copy

    ASGHARI MOGHADDAM A., NORANI V., NADIRI A.O.. FORECASTING SPATIOTEMPORAL WATER LEVELS BY NEURAL KRIGING METHOD IN TABRIZ CITY UNDERGROUND AREA. IRAN-WATER RESOURCES RESEARCH[Internet]. 2009;5(1 (13)):14-24. Available from: https://sid.ir/paper/100360/en

    IEEE: Copy

    A. ASGHARI MOGHADDAM, V. NORANI, and A.O. NADIRI, “FORECASTING SPATIOTEMPORAL WATER LEVELS BY NEURAL KRIGING METHOD IN TABRIZ CITY UNDERGROUND AREA,” IRAN-WATER RESOURCES RESEARCH, vol. 5, no. 1 (13), pp. 14–24, 2009, [Online]. Available: https://sid.ir/paper/100360/en

    Related Journal Papers

    Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    مرکز اطلاعات علمی SID
    strs
    دانشگاه امام حسین
    بنیاد ملی بازیهای رایانه ای
    کلید پژوه
    ایران سرچ
    ایران سرچ
    File Not Exists.
    Move to top