Robust adaptive boosted canonical correlation analysis for quality-relevant process monitoring of wastewater treatment
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Robust adaptive boosted canonical correlation analysis for quality-relevant process monitoring of wastewater treatment
Authors
Keywords
Canonical correlation analysis (CCA), Adaptive threshold, Fault detection, Quality-relevant, Wastewater treatment
Journal
ISA TRANSACTIONS
Volume -, Issue -, Pages -
Publisher
Elsevier BV
Online
2021-01-25
DOI
10.1016/j.isatra.2021.01.039
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Learning soft sensors using time difference–based multi-kernel relevance vector machine with applications for quality-relevant monitoring in wastewater treatment
- (2020) Jing Wu et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- Rebooting data-driven soft-sensors in process industries: A review of kernel methods
- (2020) Yiqi Liu et al. JOURNAL OF PROCESS CONTROL
- Adaptive Transfer Learning of Cross-Spatiotemporal Canonical Correlation Analysis for Plant-Wide Process Monitoring
- (2020) Hongchao Cheng et al. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
- A novel fault identification and root-causality analysis of incipient faults with applications to wastewater treatment processes
- (2019) Hongchao Cheng et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- Plant-wide process monitoring by using weighted copula–correlation based multiblock principal component analysis approach and online-horizon Bayesian method
- (2019) Ying Tian et al. ISA TRANSACTIONS
- A Mixture of Variational Canonical Correlation Analysis for Nonlinear and Quality-Relevant Process Monitoring
- (2018) Yiqi Liu et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Fault Detection for Non-Gaussian Processes Using Generalized Canonical Correlation Analysis and Randomized Algorithms
- (2018) Zhiwen Chen et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Data-Driven Distributed Local Fault Detection for Large-Scale Processes Based on the GA-Regularized Canonical Correlation Analysis
- (2017) Qingchao Jiang et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Robust Principal Component Pursuit for Fault Detection in a Blast Furnace Process
- (2017) Yijun Pan et al. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
- Prediction of Filamentous Sludge Bulking using a State-based Gaussian Processes Regression Model
- (2016) Yiqi Liu et al. Scientific Reports
- Canonical variate analysis-based contributions for fault identification
- (2015) Benben Jiang et al. JOURNAL OF PROCESS CONTROL
- Multiblock Concurrent PLS for Decentralized Monitoring of Continuous Annealing Processes
- (2014) Qiang Liu et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Statistical Monitoring of Wastewater Treatment Plants Using Variational Bayesian PCA
- (2014) Yiqi Liu et al. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
- Plant-wide process monitoring based on mutual information–multiblock principal component analysis
- (2014) Qingchao Jiang et al. ISA TRANSACTIONS
- Review of Recent Research on Data-Based Process Monitoring
- (2013) Zhiqiang Ge et al. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
- Robust Recovery of Subspace Structures by Low-Rank Representation
- (2012) Guangcan Liu et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- ICA and me – A subjective review
- (2012) Gustaf Olsson WATER RESEARCH
- Robust principal component analysis?
- (2011) Emmanuel J. Candès et al. JOURNAL OF THE ACM
- Reconstruction-based contribution for process monitoring
- (2009) Carlos F. Alcala et al. AUTOMATICA
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now