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  • 2021

    Case studies

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 255-303 49 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Conclusion and further research directions

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 305-309 5 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Fault isolation

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 71-117 47 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Introduction

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 1-17 17 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Linear latent variable regression (LVR)-based process monitoring

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 19-70 52 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Multiscale latent variable regression-based process monitoring methods

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 155-191 37 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Nonlinear latent variable regression methods

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 119-154 36 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Unsupervised deep learning-based process monitoring methods

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 193-223 31 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Unsupervised recurrent deep learning scheme for process monitoring

    Harrou, F., Sun, Y., Hering, A. S., Madakyaru, M. & Dairi, A., 2021, Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches. Elsevier, p. 225-253 29 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • 2020

    Forecasting of Photovoltaic Solar Power Production Using LSTM Approach

    Harrou, F., Kadri, F. & Sun, Y., Apr 1 2020, Advanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems. IntechOpen

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • Functional Data Visualization

    Genton, M. G. & Sun, Y., Nov 4 2020, Wiley StatsRef: Statistics Reference Online. Wiley, p. 1-11 11 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • 2019

    Spatial Models Using Laplace Approximation Methods

    Gómez-Rubio, V., Bivand, R. S. & Rue, H., May 16 2019, Handbook of Regional Science. Springer Berlin Heidelberg, p. 1-16 16 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  • 2017

    An Improved Wavelet-Based Multivariable Fault Detection Scheme

    Harrou, F., Sun, Y. & Madakyaru, M., Jul 5 2017, Uncertainty Quantification and Model Calibration. IntechOpen

    Research output: Chapter in Book/Report/Conference proceedingChapter