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:

606
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:

Information Journal Paper

Title

Assessment of Ordered Weighted Averaging Strategies in Combination of Streamflow Forecasting Models Case study: Karkheh River

Pages

  15-25

Abstract

 Monthly streamflow forecasting plays an important role in long-lead water resources planning and management. In the current paper, Model fusion technique has been used in order to increase the accuracy of monthly streamflow forecast of Karkheh River at the entrance of Karkheh reservoir in winter. For this purpose, five models including: Artificial Neural Network (ANN), Generalized Regression Neural Network (GRNN), Support Vector Regression (SVR), K-Nearest Neighbor (KNN), and Linear Regression (LR) with optimized structure have been applied as individual forecasting models (IFMs). In order to combine the IFM models, two Model fusion strategies including constant and Variable Weighting based on Ordered Weighted Averaging (OWA) have been performed, where the Orlike Method has been applied to determine the weights of IFMs. The results show that variables weighting strategy is more performable than constant weighting strategy in order to promote the accuracy of the forecast results. In addition, the comparison of the two strategies including Model fusion with artificial neural network and selecting the best IFM reveals that Variable Weighting strategy can significantly promote the accuracy of the forecast results than the latest strategies; such that this strategy increases the accuracy of the results 51. 8, 38. 1, and 44. 5 percent as compared to ANN Model fusion, and 7. 6, 132, and 52. 9 percent as compared to the best IFM for January, February, and March, respectively.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    MODARESI, F., ARAGHINEJAD, S., & EBRAHIMI, K.. (2017). Assessment of Ordered Weighted Averaging Strategies in Combination of Streamflow Forecasting Models Case study: Karkheh River. IRANIAN JOURNAL OF WATERSHED MANAGEMENT SCIENCE AND ENGINEERING, 10(35 ), 15-25. SID. https://sid.ir/paper/134792/en

    Vancouver: Copy

    MODARESI F., ARAGHINEJAD S., EBRAHIMI K.. Assessment of Ordered Weighted Averaging Strategies in Combination of Streamflow Forecasting Models Case study: Karkheh River. IRANIAN JOURNAL OF WATERSHED MANAGEMENT SCIENCE AND ENGINEERING[Internet]. 2017;10(35 ):15-25. Available from: https://sid.ir/paper/134792/en

    IEEE: Copy

    F. MODARESI, S. ARAGHINEJAD, and K. EBRAHIMI, “Assessment of Ordered Weighted Averaging Strategies in Combination of Streamflow Forecasting Models Case study: Karkheh River,” IRANIAN JOURNAL OF WATERSHED MANAGEMENT SCIENCE AND ENGINEERING, vol. 10, no. 35 , pp. 15–25, 2017, [Online]. Available: https://sid.ir/paper/134792/en

    Related Journal Papers

    Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    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