To solve the low prediction accuracy of curdlan concentration during Agrobacterium sp. fermentation, a new hybrid model based on fuzzy weighted LSSVM (least squares support vector machine) algorithm and a mechanism model was proposed. Firstly, the LSSVM algorithm was optimized by adding fuzzy weighted idea and using a mixed kernel function. The optimized LSSVM was used to solve the kinetic model of fermentation process of Agrobacterium sp. Bird swarm algorithm (BSA) was used to optimize the kinetic model parameters. The correlation functioned model between dissolved oxygen tension and various parameters was summarized and substituted into the kinetic model. A hybrid fermentation kinetic model that used dissolved oxygen tension as a key control variable was established. Finally, the BSA was used to find a controlling strategy for the optimal process of dissolving oxygen that maximized curdlan concentration. The results demonstrated that the prediction accuracy of hybrid model improved. When the dissolved oxygen concentration in the polysaccharide-producing period was 52%, the curdlan concentration reached the highest (48.85 g/L). The hybrid model of Agrobacterium fermentation process established in this study together with the results of optimized dissolved oxygen provided a direction for fermentation industries to further improve the yield of polysaccharides through optimal dissolved oxygen controlling strategy.
SHAO Yuqian
,
ZONG Yuan
,
LIU Yian
,
LIU Dengfeng
. Hybrid modeling and optimization of Agrobacterium fermentation process based on a mechanism model and fuzzy weighted LSSVM algorithm[J]. Food and Fermentation Industries, 2019
, 45(7)
: 65
-73
.
DOI: 10.13995/j.cnki.11-1802/ts.018877
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