[Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini].
OBJECTIVE
To introduce Back-propagation (BP) neural network and genetic algorithm for multi-objective optimization of extraction technology of Cortex Fraxini.


METHODS
BP neural network was established and optimized with uniform design. Genetic algotithm was used for multi-objective optimization of extraction technology of cortex fraxini.


RESULTS
the 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%.


CONCLUSIONS
Back-propagation neural network and genetic algorithm for multi-objective optimization of extraction technology of cortex fraxini is advisable.
Yang
Ming
M
Medicament Department Of Longhua Hospital Affiliated to Shanghai Univesity of Traditional Chinese Medicine, Shanghai 200032, China. yangpluszhu@sina.com
Yu
Min-ying
MY
Shi
Xiu-feng
XF
Teng
Yan-ping
YP
D031319:Aesculus; D000465:Algorithms; D004365:Drugs, Chinese Herbal / Q000737:chemistry*; D016571:Neural Networks, Computer
D004365:Drugs, Chinese Herbal; C517354:horse chestnut seed