An Improved Most Valuable Player Algorithm with Twice Training Mechanism

Faculty Computer Science Year: 2018
Type of Publication: ZU Hosted Pages:
Authors:
Mohammed Abdel Basset Metwally Attia
Journal: Lecture Notes in Computer Science Springer‏ Volume:
Keywords : , Improved Most Valuable Player Algorithm with    
Abstract:
The most valuable player algorithm is inspired from these players who want to win the Most Valuable Player (MVP) trophy, it have higher overall success percentage. Teaching-learning-based optimization (TLBO) simulates the process of teachin
    
     
 
       

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  • Mohammed Abdel Basset Metwally Attia, "A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems", Springer London, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection", Pergamon, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient teaching-learning-based optimization algorithm for parameters identification of photovoltaic models: Analysis and validations", Pergamon, 2021 More

Department Related Publications

  • Saber Mohamed, "A surrogate-assisted differential evolution algorithm with dynamic parameters selection for solving expensive optimization problems", IEEE, 2014 More
  • Saber Mohamed, "Differential Evolution Combined with Constraint Consensus for Constrained Optimization", IEEE, 2011 More
  • Noha Mohamed Ibrahiem Mohamed Hamza, "A constraint consensus memetic algorithm for solving constrained optimization problems", Taylor & Francis, 2014 More
  • Mohammed Abdel Basset Metwally Attia, "An approach of TOPSIS technique for developing supplier selection with group decision making under type-2 neutrosophic number", Elsevier B.V., 2019 More
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