生物发酵过程效益函数的在线预报  

The On-line Prediction of Profit Function for Fed-Batch Bioprocesses

作　　者：李运锋[1] 袁景淇[1] 

机构地区：[1]上海交通大学自动化系,上海200030

出　　处：《上海交通大学学报》2005年第8期1341-1343,1348,共4页Journal of Shanghai Jiaotong University

基　　金：国家高技术研究发展计划(863)项目(2001AA413110);国家自然科学基金资助项目(60174024)

摘　　要：提出了一种基于神经网络的效益函数预报方法.为了提高预报精度,引入滚动学习预报技术处理过程的时变性.该预报技术中,输入输出数据对通过移动窗口获得.在每一次采样时间后,由输入输出数据对构成的训练数据库将被更新,然后程序重复进行下一轮的预报.为检验所提出方法的有效性,以头孢菌素C生产为例,对效益函数进行了超前24h预报,结果显示该方法的预报精度高于已有的方法.A novel approach for the on-line prediction of the profit function was proposed based on neural networks. In order to improve the prediction accuracy, a rolling learning-prediction procedure was introduced to deal with the time variant property of the bioprocess. In this procedure, the input-output data pair is obtained using a moving data windows technique. The training database, which is composed of the set of input-output data pairs, is updated after each sampling interval, and the learning-prediction is repeated thereafter. To test the validity of the proposed approach, the profit function in Cephalosporin C fedbatch cultivation is predicted 24 hours ahead as an example. The result indicates the proposed approach outperforms the previous method in prediction accuracy.

关 键 词：发酵过程 神经网络 效益函数 预报 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]