Title :
Soft-sensing method based on modified ANN inversion and its application in erythromycin fermentation
Author :
Ding, Yuhan ; Liu, Guohai ; Dai, Xianzhong
Author_Institution :
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
Abstract :
In this paper, we modify the soft-sensing method based on ANN inversion. By using the non-state variables or the so-called function variables besides the state variables, the possibility in constructing the soft-sensing model will increase and the derivative order in soft-sensing model will be low. The simulation results verify that the soft-sensing method based on the modified ANN inversion is more accurate than the unmodified one.
Keywords :
biotechnology; fermentation; neural nets; pharmaceutical industry; artificial neural network; erythromycin fermentation; function variables; modified ANN inversion; soft-sensing method; state variables; Artificial neural networks; Educational institutions; Equations; Mathematical model; Noise; Sensors; Training; Soft sensing; erythromycin fermentation; modified ANN inversion;
Conference_Titel :
Information and Automation (ICIA), 2012 International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4673-2238-6
Electronic_ISBN :
978-1-4673-2236-2
DOI :
10.1109/ICInfA.2012.6246910
