Determination of optimal process parameters to prepare licorice extract micro-particles using artificial neural network based particle swarm optimization

Honghao Zhang, Guangdong Tian, Mengchu Zhou, Chaoyong Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages787-791
Number of pages5
ISBN (Electronic)9781467384148
DOIs
StatePublished - Sep 27 2016
Event12th World Congress on Intelligent Control and Automation, WCICA 2016 - Guilin, China
Duration: Jun 12 2016Jun 15 2016

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)
Volume2016-September

Other

Other12th World Congress on Intelligent Control and Automation, WCICA 2016
Country/TerritoryChina
CityGuilin
Period6/12/166/15/16

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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