Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini.
- Author:
Ming YANG
1
;
Min-ying YU
;
Xiu-feng SHI
;
Yan-ping TENG
Author Information
- Publication Type:Journal Article
- MeSH: Algorithms; Drugs, Chinese Herbal; chemistry; Neural Networks (Computer)
- From: China Journal of Chinese Materia Medica 2008;33(22):2622-2626
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo introduce Back-propagation (BP) neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini.
METHODBP neural network was established and optimized with uniform design. Genetic algotithm was used for multi-objective optimization of extraction technology of cortex fraxini.
RESULTthe optimization of extraction was as follows: extraction temperature was 99 degrees C, concentration of EtOH was 50%, liquid-solid ratio was 7, extraction time was 94 min. The proportional error between predictive value and practical measured value was just -1.16% and -5.14%.
CONCLUSIONBack-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of cortex fraxini is advisable.
