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:

340
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

Meteorological Drought Analysis Using Particle Swarm Optimization Algorithm-Artificial Neural Networks Based on MSPI Index

Pages

  107-120

Abstract

 The drought phenomenon is one of the natural disasters, which may occur in all climatic zones and cause serious damages to the environment and human life. So, forecasting this phenomenon may have significant impact on the water resources management and reduce its destructive effects as much as possible. In this study, the Multivariate standardized precipitation index (MSPI) was utilized to compute the drought characteristics in the Lighvanchai basin and then the Artificial neural network (ANN) was used to forecast the MSPI values. In order to train the ANN and estimate its optimized weights, the particle swarm optimization (PSO) algorithm was applied and its performance was compared with the backpropagation (BP) algorithm. In this context, different scenarios and structures were considered and then the goodness-of-fit tests were utilized for evaluating the accuracy of them. The results demonstrated that the ANN-PSO model had a better performance than the ANN-BP model for drought forecasting.

Cites

  • No record.
  • References

  • No record.
  • Cite

    APA: Copy

    SHAFIEI NAJD, M., HASSANZADEH, Y., ALAMI, M.T., & ABDI KORDANI, A.. (2018). Meteorological Drought Analysis Using Particle Swarm Optimization Algorithm-Artificial Neural Networks Based on MSPI Index. WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), 28(2 ), 107-120. SID. https://sid.ir/paper/147910/en

    Vancouver: Copy

    SHAFIEI NAJD M., HASSANZADEH Y., ALAMI M.T., ABDI KORDANI A.. Meteorological Drought Analysis Using Particle Swarm Optimization Algorithm-Artificial Neural Networks Based on MSPI Index. WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE)[Internet]. 2018;28(2 ):107-120. Available from: https://sid.ir/paper/147910/en

    IEEE: Copy

    M. SHAFIEI NAJD, Y. HASSANZADEH, M.T. ALAMI, and A. ABDI KORDANI, “Meteorological Drought Analysis Using Particle Swarm Optimization Algorithm-Artificial Neural Networks Based on MSPI Index,” WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE), vol. 28, no. 2 , pp. 107–120, 2018, [Online]. Available: https://sid.ir/paper/147910/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