To cite metANN in publications, please use: References for implemented optimization algorithms and neural network components: References for metaheuristic-based neural network training:

Dilber B, Ozdemir A (2026). metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems. R package version 0.1.0, https://github.com/burakdilber/metANN.

Kennedy J, Eberhart R (1995). “Particle Swarm Optimization.” In Proceedings of ICNN'95 - International Conference on Neural Networks, volume 4, 1942–1948. doi:10.1109/ICNN.1995.488968.

Storn R, Price K (1997). “Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces.” Journal of Global Optimization, 11, 341–359. doi:10.1023/A:1008202821328.

Goldberg D (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA.

Karaboga D, Basturk B (2007). “A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm.” Journal of Global Optimization, 39, 459–471. doi:10.1007/s10898-007-9149-x.

Mirjalili S, Mirjalili S, Lewis A (2014). “Grey Wolf Optimizer.” Advances in Engineering Software, 69, 46–61. doi:10.1016/j.advengsoft.2013.12.007.

Mirjalili S, Lewis A (2016). “The Whale Optimization Algorithm.” Advances in Engineering Software, 95, 51–67. doi:10.1016/j.advengsoft.2016.01.008.

Rao R, Savsani V, Vakharia D (2011). “Teaching-Learning-Based Optimization: A Novel Method for Constrained Mechanical Design Optimization Problems.” Computer-Aided Design, 43, 303–315. doi:10.1016/j.cad.2010.12.015.

Fu Y, Liu D, Chen J, He L (2024). “Secretary Bird Optimization Algorithm: A New Metaheuristic for Solving Global Optimization Problems.” Artificial Intelligence Review, 57, 123. doi:10.1007/s10462-024-10729-y.

Kingma D, Ba J (2015). “Adam: A Method for Stochastic Optimization.” In International Conference on Learning Representations.

Nair V, Hinton G (2010). “Rectified Linear Units Improve Restricted Boltzmann Machines.” In Proceedings of the 27th International Conference on Machine Learning, 807–814.

Bridle J (1990). “Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition.” In Neurocomputing: Algorithms, Architectures and Applications, 227–236. Springer.

Montana D, Davis L (1989). “Training Feedforward Neural Networks Using Genetic Algorithms.” In Proceedings of the 11th International Joint Conference on Artificial Intelligence, 762–767.

Ilonen J, Kamarainen J, Lampinen J (2003). “Differential Evolution Training Algorithm for Feed-Forward Neural Networks.” Neural Processing Letters, 17, 93–105. doi:10.1023/A:1022995128597.

Karaboga D, Ozturk C (2009). “Neural Networks Training by Artificial Bee Colony Algorithm on Pattern Classification.” Neural Network World, 19(3), 279–292.

Mirjalili S (2015). “How Effective is the Grey Wolf Optimizer in Training Multi-Layer Perceptrons.” Applied Intelligence, 43, 150–161. doi:10.1007/s10489-014-0645-7.

Dilber B, Ozdemir A (2026). “A novel approach to training feed-forward multi-layer perceptrons with recently proposed secretary bird optimization algorithm.” Neural Computing and Applications, 38(5). doi:10.1007/s00521-026-11874-x.

Corresponding BibTeX entries:

  @Manual{,
    title = {metANN: Metaheuristic and Gradient-Based Optimization for
      Neural Network Training and Continuous Problems},
    author = {Burak Dilber and A. Firat Ozdemir},
    year = {2026},
    note = {R package version 0.1.0},
    url = {https://github.com/burakdilber/metANN},
  }

  @InProceedings{,
    title = {Particle Swarm Optimization},
    author = {James Kennedy and Russell Eberhart},
    booktitle = {Proceedings of ICNN'95 - International Conference on
      Neural Networks},
    year = {1995},
    volume = {4},
    pages = {1942--1948},
    doi = {10.1109/ICNN.1995.488968},
  }

  @Article{,
    title = {Differential Evolution -- A Simple and Efficient Heuristic
      for Global Optimization over Continuous Spaces},
    author = {Rainer Storn and Kenneth Price},
    journal = {Journal of Global Optimization},
    year = {1997},
    volume = {11},
    pages = {341--359},
    doi = {10.1023/A:1008202821328},
  }

  @Book{,
    title = {Genetic Algorithms in Search, Optimization, and Machine
      Learning},
    author = {David E. Goldberg},
    publisher = {Addison-Wesley},
    address = {Reading, MA},
    year = {1989},
  }

  @Article{,
    title = {A Powerful and Efficient Algorithm for Numerical Function
      Optimization: Artificial Bee Colony (ABC) Algorithm},
    author = {Dervis Karaboga and Bahriye Basturk},
    journal = {Journal of Global Optimization},
    year = {2007},
    volume = {39},
    pages = {459--471},
    doi = {10.1007/s10898-007-9149-x},
  }

  @Article{,
    title = {Grey Wolf Optimizer},
    author = {Seyedali Mirjalili and Seyed Mohammad Mirjalili and
      Andrew Lewis},
    journal = {Advances in Engineering Software},
    year = {2014},
    volume = {69},
    pages = {46--61},
    doi = {10.1016/j.advengsoft.2013.12.007},
  }

  @Article{,
    title = {The Whale Optimization Algorithm},
    author = {Seyedali Mirjalili and Andrew Lewis},
    journal = {Advances in Engineering Software},
    year = {2016},
    volume = {95},
    pages = {51--67},
    doi = {10.1016/j.advengsoft.2016.01.008},
  }

  @Article{,
    title = {Teaching-Learning-Based Optimization: A Novel Method for
      Constrained Mechanical Design Optimization Problems},
    author = {R. V. Rao and V. J. Savsani and D. P. Vakharia},
    journal = {Computer-Aided Design},
    year = {2011},
    volume = {43},
    pages = {303--315},
    doi = {10.1016/j.cad.2010.12.015},
  }

  @Article{,
    title = {Secretary Bird Optimization Algorithm: A New Metaheuristic
      for Solving Global Optimization Problems},
    author = {Youfa Fu and Dan Liu and Jiadui Chen and Ling He},
    journal = {Artificial Intelligence Review},
    year = {2024},
    volume = {57},
    pages = {123},
    doi = {10.1007/s10462-024-10729-y},
  }

  @InProceedings{,
    title = {Adam: A Method for Stochastic Optimization},
    author = {Diederik P. Kingma and Jimmy Ba},
    booktitle = {International Conference on Learning Representations},
    year = {2015},
  }

  @InProceedings{,
    title = {Rectified Linear Units Improve Restricted Boltzmann
      Machines},
    author = {Vinod Nair and Geoffrey E. Hinton},
    booktitle = {Proceedings of the 27th International Conference on
      Machine Learning},
    year = {2010},
    pages = {807--814},
  }

  @InCollection{,
    title = {Probabilistic Interpretation of Feedforward Classification
      Network Outputs, with Relationships to Statistical Pattern
      Recognition},
    author = {John S. Bridle},
    booktitle = {Neurocomputing: Algorithms, Architectures and
      Applications},
    publisher = {Springer},
    year = {1990},
    pages = {227--236},
  }

  @InProceedings{,
    title = {Training Feedforward Neural Networks Using Genetic
      Algorithms},
    author = {D. J. Montana and L. Davis},
    booktitle = {Proceedings of the 11th International Joint Conference
      on Artificial Intelligence},
    year = {1989},
    pages = {762--767},
  }

  @Article{,
    title = {Differential Evolution Training Algorithm for Feed-Forward
      Neural Networks},
    author = {J. Ilonen and J.-K. Kamarainen and J. Lampinen},
    journal = {Neural Processing Letters},
    year = {2003},
    volume = {17},
    pages = {93--105},
    doi = {10.1023/A:1022995128597},
  }

  @Article{,
    title = {Neural Networks Training by Artificial Bee Colony
      Algorithm on Pattern Classification},
    author = {D. Karaboga and C. Ozturk},
    journal = {Neural Network World},
    year = {2009},
    volume = {19},
    number = {3},
    pages = {279--292},
  }

  @Article{,
    title = {How Effective is the Grey Wolf Optimizer in Training
      Multi-Layer Perceptrons},
    author = {S. Mirjalili},
    journal = {Applied Intelligence},
    year = {2015},
    volume = {43},
    pages = {150--161},
    doi = {10.1007/s10489-014-0645-7},
  }

  @Article{,
    title = {A novel approach to training feed-forward multi-layer
      perceptrons with recently proposed secretary bird optimization
      algorithm},
    author = {Burak Dilber and A. Firat Ozdemir},
    journal = {Neural Computing and Applications},
    year = {2026},
    volume = {38},
    number = {5},
    doi = {10.1007/s00521-026-11874-x},
  }