- All Journals
- Al-Qadisiyah University
- Basrah University
- Kirkuk University
- Mosul University
- The Iraqi Borad for Medical Specialization
- University of Anbar
- University of Technology
- Al Mustafa University
- Al-Zahraa University for Women
- Alnoor University
- Kunooz University
- Misan University
- Ninevah University
- Tikrit University
- University of Al-Hamdaniya
- University of Kerbala
Application of the black hole algorithm on data clustering using the big bang algorithm | ||
| Al-Qadisiyah Journal for Engineering Sciences | ||
| Articles in Press, Accepted Manuscript, Available Online from 12 April 2026 PDF (7.06 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.30772/qjes.2026.166848.1805 | ||
| Author | ||
| Dalal Jameel F. Aljasim* | ||
| Department of Computer Engineering, Islamic Azad University, Isfahan, Iran. | ||
| Abstract | ||
| Character-inspired algorithms have win meaningful traction in current age due to their healthy ability to resolve complex growth problems. This influence is achieved through their elasticity expected employed either alone or together with different algorithms or techniques. Between these, the Abyss optimization invention is conspicuous as a meta-heuristic approach stimulated by the huge wonder of black dents, which arise from heroes of immense intensity and gravitational capacity. The Black Hole invention begins accompanying a community of potential solutions, evaluating ruling class to identify highest in rank candidate, named as the "abyss." Subsequent resolutions, represented as "favorites," are evenly absorbed for one abyss as part of the addition process. In our proposed augmentations, we brought in a novel method for create heroes that are absorbed for one black hole, alongside modifications to star evolution movement to boost exploration proficiencies. These adjustments were particularly planned to improve the invention's conduct in data assembling tasks, even in scenarios deficient forethought about the dataset's characteristics. To corroborate the influence of these modifications, we conducted far-reaching evaluations using diversified standard datasets and statistical study techniques. The exploratory results showed that the enhanced treasure usually delivers superior act compared to various widely-secondhand optimization procedures, showcasing allure promise in engaging in challenging addition questions. | ||
| Keywords | ||
| Black hole; Data clustering; Big Bang algorithm; Machine learning; Optimization algorithm | ||
|
Statistics Article View: 105 PDF Download: 41 |
||