• DocumentCode
    3391999
  • Title

    Using AWPSO to Solve the Data Scarcity Problem in Wind Speed Prediction by Artificial Neural Networks

  • Author

    Fesharaki, Mohsen ; Shafiabady, Niusha ; Fesharaki, Mohsen A. ; Ahmadi, Shahab

  • Author_Institution
    Sci. Soc. of Mechatron., Azad Univ., Azad, Iran
  • Volume
    3
  • fYear
    2010
  • fDate
    23-24 Oct. 2010
  • Firstpage
    49
  • Lastpage
    52
  • Abstract
    A new strategy in wind speed prediction based on adaptive weighted particle swarm optimization combined with artificial neural networks was proposed. Regarding the data gathering, sometimes it is difficult to provide the neural network with sufficient data to be trained efficiently. In order to solve this problem Adaptive weighed particle swarm optimization is used to increase the data the produced data is fed to a multilayered feed forward neural network to predict the future wind speed. This method has lead to good estimated wind speed accuracy and good prediction performance.
  • Keywords
    data acquisition; feedforward neural nets; particle swarm optimisation; wind power; AWPSO; adaptive weighted particle swarm optimization; artificial neural network; data scarcity problem; multilayered feed forward neural network; wind speed prediction; Artificial neural networks; Neurons; Particle swarm optimization; Simulation; Wind power generation; Wind speed; Wind turbines; Adaptive Weighted Particle Swarm Optimization; Data Scarcity; Multilayered Feed Forward Neural Network; Prediction; Wind Speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-8432-4
  • Type

    conf

  • DOI
    10.1109/AICI.2010.251
  • Filename
    5655134