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

Persian Verion

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

video

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

sound

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

Persian Version

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

View:

1,133
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

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

Cites:

1

Information Journal Paper

Title

PREDICTING STREAMFLOW USING DATA-DRIVEN MODEL AND TIME SERIES

Pages

  167-179

Abstract

 Accurate forecasting of streamflows has been one of the most important issues playing a key role in allotment of water resources. RIVER FLOW simulations to determine the future RIVER FLOWs are important and practical. Given the importance of flow in the coming years, in this research three stations were simulated in 2002-2011: Haji Qooshan, Ghare Shoor and Tamar in GORGANROOD Cachment. To simulate RIVER FLOW, TIME SERIES (Auto Regression) and data driven based on SUPPORT VECTOR MACHINE (SVM) was used for both monthly and weekly. The results showed that both methods in Tamar have low precision and Haji Qooshan station have good precision in monthly simulation. SVM increase 0.29 coefficient determination and decreases 0.35 RMSE error in Ghare Shoor station and perform more accurate than TIME SERIES. Both methods simulate weekly discharge in low precision in Tamar and Ghare Shoor. Coefficient determination of TIME SERIES is 0.91 and SVM is 0.86 in weekly simulation. DDR statistics show that the SVM has greater precision than TIME SERIES in monthly simulation and equal precision in weekly simulation in Haji Qooshan station. The results of this study show that the SVM method is more accurate than TIME SERIES in monthly and weekly simulation. The accuracy of both methods is on monthly basis rather than weekly. The accuracy of both methods is greater on monthly rather than weekly.

Cites

References

  • No record.
  • Cite

    APA: Copy

    SEYEDIAN, SEYED MORTEZA, SOLEIMANI, MARYAM, & KASHANI, MOJTABA. (2015). PREDICTING STREAMFLOW USING DATA-DRIVEN MODEL AND TIME SERIES. IRANIAN JOURNAL OF ECOHYDROLOGY, 1(3), 167-179. SID. https://sid.ir/paper/254226/en

    Vancouver: Copy

    SEYEDIAN SEYED MORTEZA, SOLEIMANI MARYAM, KASHANI MOJTABA. PREDICTING STREAMFLOW USING DATA-DRIVEN MODEL AND TIME SERIES. IRANIAN JOURNAL OF ECOHYDROLOGY[Internet]. 2015;1(3):167-179. Available from: https://sid.ir/paper/254226/en

    IEEE: Copy

    SEYED MORTEZA SEYEDIAN, MARYAM SOLEIMANI, and MOJTABA KASHANI, “PREDICTING STREAMFLOW USING DATA-DRIVEN MODEL AND TIME SERIES,” IRANIAN JOURNAL OF ECOHYDROLOGY, vol. 1, no. 3, pp. 167–179, 2015, [Online]. Available: https://sid.ir/paper/254226/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
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button