Package: metANN
Title: Metaheuristic and Gradient-Based Optimization for Neural Network
        Training and Continuous Problems
Version: 0.1.0
Authors@R: c(
    person(given = "Burak",
           family = "Dilber",
           email = "burakdilber91@gmail.com",
           role = c("aut", "cre", "cph")),
    person(given = "A. Fırat",
           family = "Özdemir",
           role = c("aut", "ths"))
    )
Description: Provides tools for general-purpose continuous optimization and feed-forward artificial neural network training using metaheuristic and gradient-based optimization algorithms. The package supports benchmark function optimization, regression, binary classification, and multi-class classification with multilayer perceptrons. The package implements several optimization methods, including particle swarm optimization Kennedy and Eberhart (1995) <doi:10.1109/ICNN.1995.488968>, differential evolution Storn and Price (1997) <doi:10.1023/A:1008202821328>, grey wolf optimizer Mirjalili et al. (2014) <doi:10.1016/j.advengsoft.2013.12.007>, secretary bird optimization Fu et al. (2024) <doi:10.1007/s10462-024-10729-y>, and Adam Kingma and Ba (2015) <doi:10.48550/arXiv.1412.6980>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
URL: https://github.com/burakdilber/metANN
BugReports: https://github.com/burakdilber/metANN/issues
NeedsCompilation: no
Packaged: 2026-05-11 19:24:56 UTC; hp
Author: Burak Dilber [aut, cre, cph],
  A. Fırat Özdemir [aut, ths]
Maintainer: Burak Dilber <burakdilber91@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-15 20:30:07 UTC
Built: R 4.5.2; ; 2026-05-15 21:57:12 UTC; unix
