Chapter 5 - Optimizing Biomedical Applications Using Particle Swarm Optimization: A Comprehensive Review (INTERNATIONAL STUDIES IN ENGINEERING JUNE 2025)
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Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Kitap Adı | INTERNATIONAL STUDIES IN ENGINEERING JUNE 2025 |
| Bölüm(ler) | Chapter 5 - Optimizing Biomedical Applications Using Particle Swarm Optimization: A Comprehensive Review |
| Bölüm Sayfaları | 67-88 |
| Kitap Türü | Kitap Bölümü |
| Kitap Alt Türü | Alanında uluslararası yayınlanan kitap bölümü |
| Kitap Niteliği | Diğer uluslararası bilimsel kitap |
| Kitap Dili | İngilizce |
| Basım Tarihi | 01-2025 |
| ISBN | 978-625-5897-38-1 |
| Basıldığı Ülke | Türkiye |
| Basıldığı Şehir | Ankara |
| Kitap Linki | https://www.seruvenyayinevi.com/Webkontrol/uploads/Fck/engineeringhaz25v3_1.pdf |
| Özet |
| In recent years, the problems encountered in the fields of science and engineering have become increasingly complex, thereby reducing the effectiveness of classical optimization methods. Particularly in health sciences and medical technologies, the challenges often involve nonlinear, high-dimensional, and multivariable complex systems. As a result, finding optimal solutions using conventional approaches is frequently impractical or computationally expensive. In such cases, the application of heuristic and metaheuristic optimization techniques has emerged as a significant alternative, o ering robust solutions with reduced computational burden.(Zhu et al., 2025).Metaheuristic methods are nature-inspired algorithms known for their ability to provide e ective and rapid solutions to complex and large-scale problems. Among these techniques, Genetic Algorithms, Ant Colony Optimization, Simulated Annealing, and Particle Swarm Optimization (PSO) are frequently utilized in a wide range of applications. Rather than exhaustively analyzing the entire system, these methods exploit available system information to e ciently explore the search space and discover global or near-global optimal solutions (Tang & Zhang, 2025). |
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