基于支持向量机的古龙酸发酵过程产量预报
Product prediction based on SVM in industrial 2-keto-L-gulonic acid fermentation process
维生素C的一个重要前体2-酮基-L-古龙酸(2-keto-L-Gulonic acid，简称古龙酸)，由巨大芽孢杆菌和氧化葡萄糖酸杆菌混菌流加发酵生成。由于两种菌体的相互作用机制较复杂，对发酵过程建立精确的动力学模型较困难。本文建立数据驱动模型，采用支持向量机技术对工业发酵过程的古龙酸产量进行拟在线预报，并利用滚动学习-预报技术处理过程的时变特性，结果表明该方法有较好的预报精度和鲁棒性。基于产量的超前预报结果，实现对发酵过程异常批次的早发现。
Fed-batch fermentation of Bacillus megaterium and Gluconobacter oxydans is applied to produce 2-keto-L-gulonic acid (2-KGA), a key precursor for L-ascorbic acid synthesis. For such mixed cultivation, kinetic modeling is difficult because the interactions between the two strains are not well known yet. In this paper, data-driven model is built to predict the product formation and monitor the fermentation process. A rolling learning-prediction approach based on support vector machine (SVM) is found to have good prediction performance. Based on the prediction results, abnormal batches can be detected early.
袁景淇、崔蕾
生物工程学生物科学现状、生物科学发展生物科学研究方法、生物科学研究技术
维生素C2-酮基-L-古龙酸支持向量机滚动学习-预报
L-ascorbic acid2-keto-L-gulonic acidsupport vector machine rolling learning-prediction
袁景淇,崔蕾.基于支持向量机的古龙酸发酵过程产量预报[EB/OL].(2010-04-01)[2025-08-16].http://www.paper.edu.cn/releasepaper/content/201004-12.点此复制
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