Statistics

Research output

Research output per year 2011 2017 2018 2019 2020 2021 2022 2023 2023

• 8620 Citations
• 44 h-index
• 462 Article
• 77 Conference contribution
• 16 Chapter
• 1 Editorial

Research output per year

Research output per year

Search results

• 2022

  A hybrid deep learning method with attention for COVID-19 spread forecasting

  Dairi, A., Harrou, F., Sun, Y. & Khadraoui, S., Apr 2022, Artificial Intelligence Strategies for Analyzing COVID-19 Pneumonia Lung Imaging, Volume 1. IOP Publishing

  Research output: Chapter in Book/Report/Conference proceeding › Chapter

  • Neural Network 100%
  • Short-Term Memory 100%
  • Forecasting 100%
  • Attention 100%
  • Short Term Memory 100%
• 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 proceeding › Chapter

  • Deep Learning Model 100%
  • Deep Learning 100%
  • Detection 100%
  • Decision-Making 50%
  • Detection Method 50%

• 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 proceeding › Chapter

  • Research Direction 100%
  • Monitored Process 100%
  • Availability 50%
  • Anomaly Detection 50%
  • Fault Detection 50%

• 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 proceeding › Chapter

  • Fault 100%
  • Isolation 33%
  • Approach 25%
  • Detection 16%
  • Fault Detection 8%

• 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 proceeding › Chapter

  • Process Monitoring 100%
  • Electric Potential 50%
  • Fault Detection 25%
  • Simulation Mode 25%
  • Process Performance 25%

• 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 proceeding › Chapter

  • Procedure 100%
  • Monitoring 80%
  • Process Monitoring 80%
  • Regression Model 40%
  • Variables 40%

• 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 proceeding › Chapter

  • Wavelet 100%
  • Monitoring 50%
  • Univariate 33%
  • Characteristics 33%
  • Process Monitoring 33%

• 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 proceeding › Chapter

  • Nonlinear 100%
  • Nonlinearity 57%
  • Nonlinearities 57%
  • Variable Regression 57%
  • Principal Component Analysis 28%

• 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 proceeding › Chapter

  • Learning 100%
  • Autoencoder 66%
  • Learning Approach 33%
  • Simulation Mode 33%
  • Deep Learning Model 33%

• 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 proceeding › Chapter

  • Learning 100%
  • Simulation Mode 66%
  • Process Monitoring 66%
  • Multivariate Time Series 66%
  • Memory 66%
• 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 proceeding › Chapter

  • Photovoltaic System 100%
  • Long Short-Term Memory 100%
  • Production 100%
  • Short-Term Memory 100%
  • Forecasting 100%

• 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 proceeding › Chapter

  • Functional Data 100%
  • Boxplots 80%
  • Trajectory 40%
  • Tool 40%
  • Child 40%
• 2019

  A BAYESIAN MODEL FOR ACTIVATION AND CONNECTIVITY IN TASK-RELATED FMRI DATA

  Yu, Z., Prado, R., Cramer, S. C., Quinlan, E. B. & Ombao, H., Aug 30 2019, Advances in Econometrics. Emerald Publishing Limited, p. 91-132 42 p.

  Research output: Chapter in Book/Report/Conference proceeding › Chapter

  • Connectivity 100%
  • Brain 57%
  • Hemodynamic Response 42%
  • Simulation Mode 42%
  • Response Function 42%

• 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 proceeding › Chapter

  • Laplace Approximation 100%
  • Statistics 75%
  • Gaussian 25%
  • Closed Form 25%
  • Inference 25%
• 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 proceeding › Chapter

  • Fault Detection 100%
  • Partial Least Squares 100%
  • Exponentially Weighted Moving Average 75%
  • Wavelet 50%
  • Datum 50%
• 2011

  A Closer Look at Two Approaches for Analysis and Classification of Nonstationary Time Series

  Ombao, H. & Prado, R., Jan 1 2011, Statistical Methods for Modeling Human Dynamics: An Interdisciplinary Dialogue. Taylor and Francis - Balkema, p. 155-157 3 p.

  Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

  • Number 100%
  • Characteristics 100%
  • Probability Theory 100%
  • Realization 100%
  • Methodology 100%