Chaotic multi-verse optimizer-based feature selection

Faculty Science Year: 2019
Type of Publication: ZU Hosted Pages:
Authors:
Mohamed El Sayed Ahmed Muhamed
Journal: Neural Computing and Applications SPRINGER Volume:
Keywords : Chaotic multi-verse optimizer-based feature selection    
Abstract:
The multi-verse optimizer (MVO) is a new evolutionary algorithm inspired by the concepts of multi- verse theory namely, the white/black holes, which repre- sents the interaction between the universes. However, the MVO has some drawbacks
    
     
 
       

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  • Mohamed El Sayed Ahmed Muhamed, "Efficient schemes for playout latency reduction in P2P-VOD systems", Springer, 2018 More
  • Mohamed El Sayed Ahmed Muhamed, "a novel algorithm for source localization based on nonnegative matrix factroization using \alpha 'beta divergence in chochleagram", WSEAS, 2013 More
  • Mohamed El Sayed Ahmed Muhamed, "Open cluster membership probability based on K-means clustering algorithm", Springer, 2016 More

Department Related Publications

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