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Hybrid algorithms for generating optimal designs for discriminating multiple nonlinear models under various error distributional assumptions
Finding a model-based optimal design that can optimally discriminate among a class of plausible models is a difficult task because the design criterion is non-differentiable and requires 2 or more layers of nested optimization. We propose hybrid algorithms based on particle swarm optimization (PSO)...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7535070/ https://www.ncbi.nlm.nih.gov/pubmed/33017415 http://dx.doi.org/10.1371/journal.pone.0239864 |