Quadratic Mutual Information based Regression for Prediction of Quality Variable in Batch Process
Zheng Li1,2,3,4Pu Wang1,2,3,4Xuejin Gao1,2,3,4Yongsheng Qi5Huihui Gao1,2,3,4
1. Faculty of Information Technology, Beijing University of Technology2. Engineering Research Centre of Digital Community, Ministry of Education3. Beijing Laboratory for Urban Mass Transit4. Beijing Key Laboratory of Computational Intelligence and Intelligent System5. School of Electric Power, Inner Mongolia University of Technology
摘要：Quality prediction is of great importance for batch processes. Predicting quality variable is a challenging task because of various factors such as strong nonlinearity and nonGaussian exist in batch data. A quadratic mutual information based regression method is proposed to handle the problem. The proposed method takes into account higher order statistics that reveal the non-linear dependencies between the process variables and important quality variables. Furthermore, the proposed method is implemented without the hypothesis of Gaussian distribution of the dataset as in MPLS. The effectiveness of the QMIR method is illustrated by a dataset of industrial Escherichia coli fermentation process, compared with MPLS.
基金：
funded by the National Natural Science Foundation of China under grant 61640312, 61763037, and 61803005； the Natural Science Foundation of Beijing Municipality under grant 4172007 and 4192011； the Beijing Municipal Commission of Education；
会议名称：
4th International Conference on Control Engineering and Artificial Intelligence （CCEAI 2020）
会议时间：
2020-01-17
会议地点：
Singapore
- 专辑：
理工A(数学物理力学天地生); 理工C(机电航空交通水利建筑能源)
- 专题：
数学; 数学; 工业通用技术及设备
- DOI：
10.26914/c.cnkihy.2020.002791
- 分类号：
TB114.2
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