Cargando…
Prediction of Tibial Rotation Pathologies Using Particle Swarm Optimization and K-Means Algorithms
The aim of this article is to investigate pathological subjects from a population through different physical factors. To achieve this, particle swarm optimization (PSO) and K-means (KM) clustering algorithms have been combined (PSO-KM). Datasets provided by the literature were divided into three clu...
Autores principales: | Sari, Murat, Tuna, Can, Akogul, Serkan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5920439/ https://www.ncbi.nlm.nih.gov/pubmed/29597270 http://dx.doi.org/10.3390/jcm7040065 |
Ejemplares similares
-
Prediction of Pathological Subjects Using Genetic Algorithms
por: Sari, Murat, et al.
Publicado: (2018) -
A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization
por: Sun, Tao, et al.
Publicado: (2017) -
A Novel Particle Swarm Optimization Algorithm for Global Optimization
por: Wang, Chun-Feng, et al.
Publicado: (2016) -
Swarming genetic algorithm: A nested fully coupled hybrid of genetic algorithm and particle swarm optimization
por: Aivaliotis-Apostolopoulos, Panagiotis, et al.
Publicado: (2022) -
A Novel Crow Swarm Optimization Algorithm (CSO) Coupling Particle Swarm Optimization (PSO) and Crow Search Algorithm (CSA)
por: Jia, Ying-Hui, et al.
Publicado: (2021)