BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

172 related articles for article (PubMed ID: 31228723)

  • 1. Global-and-local-structure-based neural network for fault detection.
    Zhao H; Lai Z; Chen Y
    Neural Netw; 2019 Oct; 118():43-53. PubMed ID: 31228723
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Neighborhood preserving neural network for fault detection.
    Zhao H; Lai Z
    Neural Netw; 2019 Jan; 109():6-18. PubMed ID: 30388431
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.
    Mansouri M; Nounou MN; Nounou HN
    IEEE Trans Nanobioscience; 2017 Sep; 16(6):504-512. PubMed ID: 28708564
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Batch process fault detection and identification based on discriminant global preserving kernel slow feature analysis.
    Zhang H; Tian X; Deng X; Cao Y
    ISA Trans; 2018 Aug; 79():108-126. PubMed ID: 29776590
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Nonlinear process modeling via unidimensional convolutional neural networks with self-attention on global and local inter-variable structures and its application to process monitoring.
    Li S; Luo J; Hu Y
    ISA Trans; 2022 Feb; 121():105-118. PubMed ID: 33888295
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.
    Deng X; Tian X; Chen S; Harris CJ
    IEEE Trans Neural Netw Learn Syst; 2018 Mar; 29(3):560-572. PubMed ID: 28026785
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Fault Detection and Isolation of Non-Gaussian and Nonlinear Processes Based on Statistics Pattern Analysis and the
    Zhou Z; Wang J; Yang C; Wen C; Li Z
    ACS Omega; 2022 Jun; 7(22):18623-18637. PubMed ID: 35694521
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Nonlinear Support Vector Machine-Based Feature Selection Approach for Fault Detection and Diagnosis: Application to the Tennessee Eastman Process.
    Onel M; Kieslich CA; Pistikopoulos EN
    AIChE J; 2019 Mar; 65(3):992-1005. PubMed ID: 32377021
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A multi-fault diagnosis method for sensor systems based on principle component analysis.
    Zhu D; Bai J; Yang SX
    Sensors (Basel); 2010; 10(1):241-53. PubMed ID: 22315537
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A novel method of combining generalized frequency response function and convolutional neural network for complex system fault diagnosis.
    Chen L; Zhang Z; Cao J
    PLoS One; 2020; 15(2):e0228324. PubMed ID: 32017780
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Decentralized adaptively weighted stacked autoencoder-based incipient fault detection for nonlinear industrial processes.
    Gao H; Huang W; Gao X; Han H
    ISA Trans; 2023 Aug; 139():216-228. PubMed ID: 37202232
    [TBL] [Abstract][Full Text] [Related]  

  • 12. GLSNN Network: A Multi-Scale Spatiotemporal Prediction Model for Urban Traffic Flow.
    Cai B; Wang Y; Huang C; Liu J; Teng W
    Sensors (Basel); 2022 Nov; 22(22):. PubMed ID: 36433477
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Bidirectional deep recurrent neural networks for process fault classification.
    Chadha GS; Panambilly A; Schwung A; Ding SX
    ISA Trans; 2020 Nov; 106():330-342. PubMed ID: 32684422
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Modified kernel principal component analysis using double-weighted local outlier factor and its application to nonlinear process monitoring.
    Deng X; Wang L
    ISA Trans; 2018 Jan; 72():218-228. PubMed ID: 29017769
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A novel deep learning based fault diagnosis approach for chemical process with extended deep belief network.
    Wang Y; Pan Z; Yuan X; Yang C; Gui W
    ISA Trans; 2020 Jan; 96():457-467. PubMed ID: 31324340
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Directional PCA for Fast Detection and Accurate Diagnosis: A Unified Framework.
    Li J; Ding D; Tsung F
    IEEE Trans Cybern; 2022 Nov; 52(11):11362-11372. PubMed ID: 33983889
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Monitoring Nonlinear and Non-Gaussian Processes Using Gaussian Mixture Model-Based Weighted Kernel Independent Component Analysis.
    Cai L; Tian X; Chen S
    IEEE Trans Neural Netw Learn Syst; 2017 Jan; 28(1):122-135. PubMed ID: 26685274
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Novel variation mode decomposition integrated adaptive sparse principal component analysis and it application in fault diagnosis.
    Geng Z; Duan X; Han Y; Liu F; Xu W
    ISA Trans; 2022 Sep; 128(Pt B):21-31. PubMed ID: 34857354
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Fault Detection of Urban Wastewater Treatment Process Based on Combination of Deep Information and Transformer Network.
    Peng C; FanChao M
    IEEE Trans Neural Netw Learn Syst; 2024 Jun; 35(6):8124-8133. PubMed ID: 37015564
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fault detection and isolation in the challenging Tennessee Eastman process by using image processing techniques.
    Hajihosseini P; Anzehaee MM; Behnam B
    ISA Trans; 2018 Aug; 79():137-146. PubMed ID: 29801925
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.