A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers.

Wu, Yan; Zhang, Hang; Li, Meng-Shan; Sheng, Sheng; Wang, Jun; Wu, Fu-An

Wu, Yan; Zhang, Hang; Li, Meng-Shan; Sheng, Sheng; Wang, Jun; Wu, Fu-An.

Afiliación

Wu Y; School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of China.
Zhang H; School of Mathematics and Computer Science, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of China.
Li MS; Sericultural Research Institute, Chinese Academy of Agricultural Sciences, Zhenjiang, Jiangsu 212018, People's Republic of China.
Sheng S; College of Physics and Electronic Information, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of China.
Wang J; College of Physics and Electronic Information, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of China.
Wu FA; School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of China.

R Soc Open Sci ; 9(1): 211419, 2022 Jan.

Article en En | MEDLINE | ID: mdl-35116155

Palabras clave

computational model; dissolution behaviour; evolutionary computation; particle dynamics

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: R Soc Open Sci Año: 2022 Tipo del documento: Article

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google