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Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines
The Particle Swarm Optimization (PSO) and Support Vector Machines (SVMs) approaches are used for predicting the thermodynamic parameters for the 1:1 inclusion complexation of chiral guests with β-cyclodextrin. A PSO is adopted for descriptor selection in the quantitative structure-property relations...
Tallennettuna:
| Päätekijät: | , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Molecular Diversity Preservation International (MDPI)
2009
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2695270/ https://ncbi.nlm.nih.gov/pubmed/19564942 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ijms10052107 |
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