Determination of optimal process parameters to prepare licorice extract micro-particles using artificial neural network based particle swarm optimization
Document Type
Conference Proceeding
Publication Date
9-27-2016
Abstract
The ways to obtain high-quality licorice extract (LE) micro-particles have a large impact on their aqueous solubility and bioavailability. Researchers have addressed their preparation and property modification problems. A new issue arises when decision-makers want to determine automatically the best process parameters to prepare them to minimize mean particle size. To do so, this work presents an intelligent decision-making method to obtain the optimal process parameters to prepare them. By using already obtained experimental data, we apply a hybrid algorithm integrating artificial neural network and particle swarm optimization to obtain the best experimental conditions for preparing LE micro-particles. The results indicate that this method is feasible and effective to determine the best process parameters.
Identifier
84991650721 (Scopus)
ISBN
[9781467384148]
Publication Title
Proceedings of the World Congress on Intelligent Control and Automation WCICA
External Full Text Location
https://doi.org/10.1109/WCICA.2016.7578579
First Page
787
Last Page
791
Volume
2016-September
Grant
51405075
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Zhang, Honghao; Tian, Guangdong; Zhou, Mengchu; and Zhang, Chaoyong, "Determination of optimal process parameters to prepare licorice extract micro-particles using artificial neural network based particle swarm optimization" (2016). Faculty Publications. 10267.
https://digitalcommons.njit.edu/fac_pubs/10267
