.png){kind=icon}
返回
Probabilistic Sequential Network for Deep Learning of Complex Process Data and Soft Sensor Application
.png){kind=icon}
PRE
AI
DOI：10.1109/TII.2018.2869899.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Soft sensing of quality/key variables is critical to the control and optimization of industrial processes. One of the main drawbacks of data-driven soft sensors is to deal with the dynamic and nonlinear characteristics of process data. This paper proposes a deep learning structure and corresponding training algorithm for the purpose of soft sensor, which is called probabilistic sequential network. The proposed modelmerges unsupervised feature extraction and supervised dynamic modeling approaches to improve the prediction performance. It is mainly based on the Gaussian-Bernoulli restricted Boltzmann machine and the recurrent neural network structure. To avoid the overfitting problem in the training procedure of deep learning algorithms, the L2 regularization and dropout technique are adopted. The new method can not only deeply extract the nonlinear feature but also widely capture dynamic characteristic of process data. Effectiveness and superiority of the newmethod are validated through an actual CO2 absorption column, compared to traditional methods.
Keyword:
Deep learning
dynamic modeling
Gaussian-Bernoulli restricted Boltzmann machine (GRBM)
nonlinear feature extraction
recurrent neural network (RNN)
soft sensor
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.9
论文数:
8.3K
被引数:
6.0W
机构
引用论文
On the Development and Applications of Cellulosic Nanofibrillar and Nanocrystalline Materials纤维素纳米原纤和纳米晶材料的发展与应用
PREAI
分享收藏分享收藏Data Mining and Analytics in the Process Industry: The Role of Machine Learning流程工业中的数据挖掘和分析: 机器学习的作用.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏On-line novelty detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditionsIEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
分享收藏Microwave dielectric spectroscopy of a single biological cell with improved sensitivity up to 40 GHzOAAI
OAAI分享收藏A Data-Driven Soft Sensor Modeling Method Based on Deep Learning and its Application基于深度学习的数据驱动软测量建模方法及应用
PREAI
分享收藏
查看更多内容