Data-driven Soft Sensors in the process industry

Keywords

Soft sensor, Process (computing), Work (physics), Engineering, Work in process

References

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Cited by

• A Data-Driven Response Virtual Sensor Technique with Partial Vibration Measurements Using Convolutional Neural NetworkShanbin Sun, Yuanyuan He, Si-Da Zhou — 2017
• Statistical Modeling Method for Efficiency Improvement of Industrial ProcessesSanghong Kim — 2014
• Multiple Model Approach for Inferential Instruments DesignElom Ayih Domlan, Biao Huang, Fangwei Xu — 2010
• Automatic control of bioprocesses.M. Stanke, Bernd Hitzmann — 2013
• On-line control of glucose feeding in an Escherichia coli fed-batch cultivation expressing a recombinant protein.Robert Gustavsson — 2011
• Optimizing kernel methods to reduce dimensionality in fault diagnosis of industrial systemsJosé Manuel Bernal de Lázaro, Alberto Prieto Moreno, Orestes Llanes‐Santiago — 2015
• Robust semi-supervised mixture probabilistic principal component regression model development and application to soft sensorsJinlin Zhu, Zhiqiang Ge, Zhihuan Song — 2015
• Electromagnetic, optical, radiation, chemical, and biomedical measurementJohn G. Webster, Halit Eren — 2014
• Adaptive database management based on the database monitoring index for long-term use of adaptive soft sensorsHiromasa Kaneko, Kimito Funatsu — 2015
• An efficient latent variable optimization approach with stochastic constraints for complex industrial processZhengshun Fei, Kangling Liu, Bin Hu — 2015
• Ensemble local kernel learning for online prediction of distributed product outputs in chemical processesYi Liu, Zhengjiang Zhang, Junghui Chen — 2015
• A New Static Estimator Based on Self-Optimizing TheoryChriss Grimholt — 2011
• Sensors signal processing under influence of environmental disturbancesSławomir Cięszczyk — 2013
• Methods for Plant Data-Based Process Modeling in Soft-Sensor DevelopmentDražen Slišković, Ratko Grbić, Željko Hocenski — 2011
• DATA-DRIVEN MODELING FOR QUALITY CONTROL IN CHEMICAL PROCESSESKuilin Chen — 2014
• Optimizing model predictive control of multi-column chromatographic processesCristian Grossmann — 2009
• Online data preprocessing in the adaptive process model building based on plant dataDražen Slišković, Ratko Grbić, Željko Hocenski — 2011
• Nonlinear feature extraction for soft sensor modeling based on weighted probabilistic PCAXiaofeng Yuan, Lingjian Ye, Liang Bao — 2015
• Co-training partial least squares model for semi-supervised soft sensor developmentLiang Bao, Xiaofeng Yuan, Zhiqiang Ge — 2015
• Data density-based fault detection and diagnosis with nonlinearities between variables and multimodal data distributionsHiromasa Kaneko, Kimito Funatsu — 2015

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