Provides an implementation of Secretary Bird Optimization for general-purpose continuous optimization, benchmark optimization, and training single-hidden-layer feed-forward neural network models. The implemented optimizer is based on the Secretary Bird Optimization Algorithm proposed by Fu et al. (2024) <doi:10.1007/s10462-024-10729-y>. The neural network training functionality is based on Dilber and Özdemir (2026) <doi:10.1007/s00521-026-11874-x>.
| Version: | 0.1.1 |
| Imports: | stats, graphics |
| Published: | 2026-05-03 |
| DOI: | 10.32614/CRAN.package.SBOAtools |
| Author: | Burak Dilber [aut, cre, cph], A. Fırat Özdemir [aut, cph] |
| Maintainer: | Burak Dilber <burakdilber91 at gmail.com> |
| BugReports: | https://github.com/burakdilber/SBOAtools/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/burakdilber/SBOAtools |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | SBOAtools results |
| Reference manual: | SBOAtools.html , SBOAtools.pdf |
| Package source: | SBOAtools_0.1.1.tar.gz |
| Windows binaries: | r-devel: SBOAtools_0.1.0.zip, r-release: SBOAtools_0.1.0.zip, r-oldrel: SBOAtools_0.1.0.zip |
| macOS binaries: | r-release (arm64): SBOAtools_0.1.0.tgz, r-oldrel (arm64): SBOAtools_0.1.0.tgz, r-release (x86_64): SBOAtools_0.1.0.tgz, r-oldrel (x86_64): SBOAtools_0.1.0.tgz |
| Old sources: | SBOAtools archive |
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