(Note: * denotes students/postdocs advised/co-advised, # denotes visiting students advised/co-advised)
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Agarwal. G.*, Tu, W., Sun, Y. and Kong, L. (2022), "Flexible quantile contours for multivariate functional data: beyond convexity," Computational Statistics and Data Analysis, 168, 107400.
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Euan, C.*, Sun, Y. and Reich, B. (2022), "Statistical analysis of multi-day solar irradiance using a threshold time series model", Environmetrics, e2716.
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Horiguchi, A., Santner T. J., Sun, Y. and Pratola, M. T. (2022), "Using BART to perform Pareto optimization and quantify its uncertainties," Technometrics, to appear.
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Wang, W.*, Sun, Y. and Wang, H. (2021), "Latent group detection in functional partially linear regression models," Biometrics, 1-12.
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Lee, J.*, Sun, Y. and Wang, H. (2021), "Spatial cluster detection with threshold quantile regression," Environmetrics, e2696.
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Hong, Y.#, Abdulah, S.*, Genton, M., and Sun, Y. (2021), "Efficiency assessment of approximated spatial predictions for large datasets,” Spatial Statistics, 43: 100517.
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Li, Y.* and Sun, Y. (2021), “Multi-site high-frequency stochastic precipitation generator using censored skew-symmetric distributions,” Spatial Statistics, 41, 100474.
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Qadir, G.*, Sun, Y. and Kurtek, S. (2021), "Estimation of spatial deformation for non-stationary processes via variogram alignment," Technometrics, 1-12.
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Agarwal, G.*, Sun, Y. and Wang, H. (2021), "Copula-based multiple indicator kriging for non-Gaussian random fields," Spatial Statistics, 44, 100524.
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Abdulah, S., Cao, Q., Pei, Y., Bosilca, G., Dongarra, J., Genton, M. G., Keyes, D. E., Ltaief, H., and Sun, Y. (2021), "Accelerating geostatistical modeling and prediction with mixed-precision computations: A high-productivity approach with PaRSEC," IEEE Transactions on Parallel and Distributed Systems, to appear.
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Huang, H., Abdulah, S., Sun, Y., Ltaief, H., Keyes, D. E., and Genton, M. G. (2021), "Competition on spatial statistics for large datasets (with discussion)," Journal of Agricultural, Biological, and Environmental Statistics, to appear.
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Salvana, M. L., Abdulah, S., Huang, H., Ltaief, H., Sun, Y., Genton, M. G., and Keyes, D. E. (2021), "High performance multivariate geospatial statistics on manycore systems," IEEE Transactions on Parallel and Distributed Systems, 32, 2719-2733.
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Qadir, G.*, Euan, C.* and Sun, Y. (2020), "Flexible modeling of variable asymmetries in cross-covariance functions for multivariate random fields," Journal of Agricultural, Biological and Environmental Statistics, 26, 1–22.
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Chen, T.*, Sun, Y. and Li, T. (2021), "A semi-parametric estimation method for the quantile spectrum with an application to earthquake classification using convolutional neural network," Computational Statistics and Data Analysis, 154, 107069.
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Chen, T.*, Sun, Y., Euan, C. and Ombao, H. (2020), "Clustering brain signals: A robust approach using functional data ranking," Journal of Classification, to appear.
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Qadir G.* and Sun, Y. (2021), "Semiparametric estimation of cross-covariance functions for multivariate random fields," Biometrics, 77, 547-560.
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Chen, W., Genton, M. G. and Sun, Y. (2021), “Space-time covariance structures and models,” Annual Review of Statistics and Its Application, 8, 191-215.
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Agarwal, G.* and Sun, Y. (2021), "Multivariate functional quantile envelopes with application to radiosonde wind data," Technometrics, 63, 2, 199-211.
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Genton, M. G., and Sun, Y. (2020), "Functional data visualization," Handbook of Computational Statistics and Data Science, Wiley StatsRef: Statistics Reference Online, 1-11.
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Chen, T.*, Sun, Y. and Maadooliat, M. (2020), "Collective spectral density estimation and clustering for spatially-correlated data,” Spatial Statistics, 38, 100451.
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Dai, W., Mrkvicka, T., Sun, Y., and Genton, M. (2020) "Functional outlier detection and taxonomy by sequential transformations," Computational Statistics and Data Analysis, 149,106960.
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Litvinenko, A., Kriemann, R., Genton, M. G., Sun, Y., and Keyes, D. (2020), "HLIBCov: Parallel hierarchical matrix approximation of large covariance matrices and likelihoods with applications in parameter identification," MethodsX, 7:100600.
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Euan, C* and Sun, Y. (2020), "Bernoulli vector autoregressive model," Journal of Multivariate Analysis, 177, 104599.
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Lee, J.*, Sun, Y. and Chang, H. (2020), "Spatial cluster detection of regression coefficient in a mixed effect model," Environmentrics, 31(2), e2578.
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Agarwal, G.*, Saade, S., Shahid, M., Test, M. and Sun, Y. (2019), "Quantile function modeling applied to salinity tolerance analysis of plant data," BMC Plant Biology, 19, 526 (2019).
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Abdulah, S.*, Ltaief, H., Sun, Y., Genton, M. G., and Keyes, D. E. (2019), “Geostatistical modeling and prediction using mixed precision tile Cholesky factorization,” IEEE International Conference on High-Performance Computing, Data, Analytics, and Data Science (HiPC), 152-162.
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Castruccio, S., Genton, M. G., and Sun, Y. (2019), "Visualising spatio-temporal models with virtual reality: From fully immersive environments to apps in stereoscopic view," Journal of the Royal Statistical Society - Series A, 182, 379-387. (read before the Royal Statistical Society, Discussion and Rejoinder)
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Euan, C.*, Sun, Y. and Ombao, H. (2019), "Coherence-based time series clustering for brain connectivity visualization," Annals of Applied Statistics, 13(2), 990-1015.
-
Euan, C.* and Sun, Y. (2019), "Directional spectra-based clustering for visualizing patterns of ocean waves and winds," Journal of Computational and Graphical Statistics, 28(3), 659-670.
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Genton, M. G., and Sun, Y. (2019), discussion of "Data science, big data, and statistics," by P. Galeano and D. Pena, TEST, 28, 338-341.
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Li, Y.* and Sun, Y. (2019), "Local likelihood estimation for nonstationary covariance functions with applications to climate model emulation," Statistica Sinica, 29, 1209-1231. (supplementary material)
-
Litvinenko, A., Sun, Y., Genton, M. G., and Keyes, D. (2019), "Likelihood approximation with hierarchical matrices for large spatial datasets," Computational Statistics and Data Analysis, 137, 115-132.
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Wang, W.* and Sun, Y. (2019), "Penalized local polynomial regression for spatial data," Biometrics, 75(4), 1179-1190.
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Tang, Y., Wang, H., Sun, Y. and Hering, A. S. (2019), "Copula-based semiparametric model for spatio-temporal data," Biometrics, 75(4), 1156-1167.
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Huang, H.* and Sun, Y. (2019), "A decomposition of total variation depth for understanding functional outliers ," Technometrics, 4, 445-458.
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Huang, H.* and Sun, Y. (2017), "Visualization and assessment of spatio-temporal covariance properties," Spatial Statistics, 34, 100272. (KAUST Discovery Highlight)
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Maadooliat, M., Sun, Y. and Chen, T.* (2018), "Collective nonparametric spectral density estimation and clustering," Statistics in Medicine, 37(30), 4789-4806.
-
Abdulah, S.*, Ltaief, H., Sun, Y., Genton, M. G., and Keyes, D. E. (2018), "ExaGeoStat: A high performance unified software for geostatistics on manycore systems," IEEE Transactions on Parallel and Distributed Systems, 29, 2778-2784. (ExaGeoStat, ExaGeoStat-R, Documentation)
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Abdulah, S.*, Ltaief, H., Sun, Y., Genton, M. G., and Keyes, D. E. (2018), "Parallel approximation of the maximum likelihood estimation for the prediction of large-scale geostatistics simulations," IEEE International Conference on Cluster Computing, 98-108.
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Sun, Y., Chang, X. and Guan, Y. (2018), "Flexible and efficient estimating equations for variogram estimation," Computational Statistics and Data Analysis, 122, 45-58.
-
Castruccio, S., Genton, M. G. and Sun, Y. (2018), "Visualising spatio-temporal models with virtual reality: from fully immersive environments to apps in stereoscopic view," Journal of the Royal Statistical Society-Series A, 182, 379-387. (to be read before the Royal Statistical Society)
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Huang, H.* and Sun, Y. (2018), "Hierarchical low rank approximation of likelihoods for large spatial datasets," Journal of Computational and Graphical Statistics, 27:1, 110-118. (KAUST Discovery Highlight)
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Yin, G.*, McCabe, M. F., Mariethoz, G. and Sun, Y. (2017), "Comparison of gap-filling methods for Landsat 7 ETM+ SLC-off imagery," International Journal of Remote Sensing, 38(23), 6653-6679.
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Meng, R.*, Saade, S., Berger. B, Brien, C., Kurtek, S., Tester, M. and Sun, Y. (2017), "Growth curve registration for evaluating salinity tolerance in barley," Plant Methods, 13-18.
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Xie, W., Kurtek, S., Bharath, K. and Sun, Y. (2017), "A Geometric approach to visualization of variability in functional data," Journal of the American Statistical Association, 112:519, 979-993. (supplementary materials) (KAUST Discovery Highlight)
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Sun, Y., Hering, A. S. and Browning, J. M. (2017), "Robust bivariate error detection in skewed data with application to historical radiosonde winds," Environmetrics , 28, e2431 . (KAUST Discovery Highlight)
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Sun, Y. and Stein, M. L. (2016), "Statistically and computationally efficient estimating equations for large spatial datasets," Journal of Computational and Graphical Statistics, 25, 187-208.
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Sun, Y., Wang, H. and Fuentes, M. (2016), "Fused adaptive Lasso for spatial and temporal quantile function estimation," Technometrics, 58, 127-137. (supplementary materials)
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Sun, Y. and Stein, M. L. (2015), "A stochastic space-time model for intermittent precipitation occurrences," Annals of Applied Statistics, 9, 2110-2132. (KAUST Discovery Highlight)
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Ngo, D., Sun, Y., Genton, M. G., Wu, J., Srinivasan, R., Cramer, S. and Ombao, H. (2015), "An exploratory data analysis of electroencephalograms using the functional boxplots approach," Frontiers in Neuroscience, 9, Article 282, 1-18. (KAUST Discovery Highlight)
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Dupuis, D. J., Sun, Y. and Wang, H. (2015), "Detecting change-points in extremes, "Statistics And Its Interface, 8, 19-31.
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Genton, M. G., Castruccio, S., Crippa, P., Dutta, S., Huser, R., Sun, Y. and Vettori, S. (2015), "Visuanimation in statistics," Stat, 4, 81-96.
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Sun, Y., Bowman, K. P., Genton, M. G., and Tokay, A. (2015), "A Matern model of the spatial covariance structure of point rain rates," Stochastic Environmental Research and Risk Assessment, 29, 411-416.
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Lopez-Pintado, S., Sun, Y., Lin, J. K., and Genton, M. G. (2014), "Simplicial band depth for multivariate functional data, " Advances in Data Analysis and Classification, 8, 321-338.
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Genton, M. G., Johnson, C., Potter, K., Stenchikov, G., and Sun, Y. (2014), "Surface boxplots," Stat, 3, 1-11. Surface boxplot software: Installation. Movie: sbplot .
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Sun, Y., Hart, J. D. and Genton, M. G. (2013), "Improved nonparametric inference for multiple correlated periodic sequences," Stat, 2, 197-210.
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Apanasovich, T. V., Genton, M. G. and Sun, Y. (2012), "A valid Matern class of cross-covariance functions for multivariate random fields with any number of components, "Journal of the American Statistical Association, 107, 180-193.
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Cooley, D., Cisewski, J., Erhardt, R. J., Jeon, S., Mannshardt, E., Omolo B. O. and Sun, Y. (2012), "A survey of spatial extremes: measuring spatial dependence and modeling spatial effects," REVSTAT, 10, 135-165.
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Sun, Y. and Genton, M. G. (2012), "Functional median polish," Journal of Agricultural, Biological, and Environmental Statistics, 17, 354-376.
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Sun, Y. and Genton, M. G. (2012), "Adjusted functional boxplots for spatio-temporal data visualization and outlier detection," Environmetrics, 23, 54-64
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Sun, Y., Genton, M. G. and Nychka, D. (2012), "Exact fast computation of band depth for large functional datasets: How quickly can one million curves be ranked?" Stat, 1, 68-74.
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Sun, Y., Hart, J. D. and Genton, M. G. (2012), "Nonparametric inference for periodic sequences," Technometrics, 54, 83-96. (ENVR Workshop Student Poster Competition Winner) R code: (CVmethod, applications).
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Sun, Y., Li, B. and Genton, M. G. (2012), "Geostatistics for large datasets, " in Advances And Challenges In Space-time Modelling Of Natural Events, J. M. Montero, E. Porcu, M. Schlather (eds), Springer, Vol. 207, Chapter 3, 55-77.
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Sun, Y. and Genton, M. G. (2011), "Functional boxplots," Journal of Computational and Graphical Statistics, 20, 316-334.(ASA Student Paper Competition Winner) R code: fbplot (fast computation), help file. Matlab code: fbplot (fast computation) .
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Xie, Y., Zhao, K., Sun, Y. and Chen, D. (2010), "Gaussian processes for short-Term traffic volume forecasting," Journal of the Transportation Research Board, 2165, 69-78.(TRB Best Paper Award)
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Sun, Y. and Lu, X. (2006), "A new method in the construction of two-level fractional factorial designs," Proceedings of the Fifth International Conference on Information and Management Sciences, Chengdu, China, 512-520.
Process Monitoring and Anomaly Detection
- Scientific books
- Harrou, F., Sun, Y. Amanda S. Hering, Madakyaru, M., and Dairi, A . (2020) Statistical Process Monitoring using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications, ISBN: 9780128193662, Publisher: Elsevier Science
- Harrou, F., Zeroual, A., Mohamad, H., Sun, Y. (2021), Advanced Road Traffic Modelling and Management Using Statistical and Deep Learning Methods, ISBN:9780128234327, Publisher: Elsevier Science
- Edited books
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Harrou, F., Sun, Y. Advanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems, IntechOpen, ISBN: 978-1-83880-092-5, April 2020.
- Published peer-reviewed papers
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Wang, W., Harrou, F., Bouyeddou, B., Senouci, S. M., and Sun, Y. (2022). Cyber-Attacks detection in industrial systems using artificial intelligence-driven methods. International Journal of Critical Infrastructure Protection (Elsevier), Accepted.
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Amin, W., Harrou, F., Dairi, A., and Sun, Y. 2022. Machine Learning and Deep Learning-Driven Methods for Predicting Ambient Particulate Matters Levels: A Case Study" to the Concurrency and Computation: Practice and Experience, e7035.
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Alkesaiberi, A., Harrou, F., Sun, Y., 2022. Efficient Wind Power Prediction Using Machine Learning Methods: A Comparative Study. Energies 2022, 15, 2327.
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Alali, Y., Harrou, F., and Sun, Y., 2022. "A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models." Scientific Reports 12.1 (2022): 1-20.
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Kadri, F., Dairi, A., Harrou, F., Sun, Y. "Towards accurate prediction of patient length of stay at emergency department: a GAN-driven deep learning framework." Journal of Ambient Intelligence and Humanized Computing (2022): 1-15.
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Dairi, A., Harrou, F., Sun, Y., 2022. Deep Generative Learning-based 1-SVM Detectors for Unsupervised COVID-19 Infection Detection Using Blood Tests, IEEE Transactions on Instrumentation & Measurement, vol. 71, pp. 1-11, 2022.
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Harrou, F., Dairi, A., Kadri, F. and Sun, Y., 2022. Effective forecasting of key features in hospital emergency department: Hybrid deep learning-driven methods. Machine Learning with Applications, p.100200.
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Wang, W., Harrou, F., Bouyeddou, B., Senouci, S.-M., Sun, Y. 2021. A stacked deep learning approach to cyber-attacks detection in industrial systems: application to power system and gas pipeline systems. Cluster Computing. doi:10.1007/s10586-021-03426-w (KAUST Discovery Highlight)
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Zerrouki, N., Dairi, A., Harrou, F., Zerrouki, Y. and Sun, Y., 2021. Efficient land desertification detection using a deep learning‐driven generative adversarial network approach: A case study. Concurrency and Computation: Practice and Experience, p.e6604.
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Dairi, A., Harrou, F., Khadraoui, S. and Sun, Y., 2021. Integrated multiple directed attention-based deep learning for improved air pollution forecasting. IEEE Transactions on Instrumentation and Measurement, 70, pp.1-15.
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Khaldi, B., Harrou, F., Benslimane, SM., and Sun, Y., 2021. A Data-Driven Soft Sensor for Swarm Motion Speed Prediction using Ensemble Learning Methods, IEEE Sensors Journal, Accepted.
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Harrou, F., Saidi, A., Sun, Y. and Khadraoui, S., 2021. Monitoring of photovoltaic systems using improved kernel-based learning schemes. IEEE Journal of Photovoltaics, 11(3), pp.806-818.
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Dairi, A., Harrou, F., Zeroual, A., Hittawe, M.M. and Sun, Y., 2021. Comparative study of machine learning methods for COVID-19 transmission forecasting. Journal of Biomedical Informatics, p.103791.
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Harrou, F., Kadri, F., Sun, Y. and Khadraoui, S., 2021. Monitoring patient flow in a hospital emergency department: ARMA-based nonparametric GLRT scheme. Health Informatics Journal, 27(2), p.14604582211021649.
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Khaldi, B., Harrou, F., Cherif, F. and Sun, Y., 2021. Towards Emerging Cubic Spline Patterns with a Mobile Robotics Swarm System", IEEE Transactions on Cognitive and Developmental Systems, Accepted.
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Taghezouit, B., Harrou, F., Sun, Y., Arab, A.H. and Larbes, C., 2021. A simple and effective detection strategy using double exponential scheme for photovoltaic systems monitoring. Solar Energy, 214, pp.337-354.
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Zerrouki, Y., Harrou, F., Zerrouki, N., Dairi, A., and Sun, Y., 2020, Desertification Detection using an Improved Variational AutoEncoder-Based Approach through ETM-Landsat Satellite Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (2020): 202-213.
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Harrou, F., Dairi, A., Kadri, F. and Sun, Y., 2020. Forecasting emergency department overcrowding: A deep learning framework. Chaos, Solitons & Fractals, 139, p.110247. (KAUST Discovery Highlight)
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Dairi, A., Harrou, F., Sun, Y. and Khadraoui, S., 2020. Short-Term Forecasting of Photovoltaic Solar Power Production Using Variational Auto-Encoder Driven Deep Learning Approach. Applied Sciences, 10(23), p.8400.
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Harrou, F., Cheng, T., Sun, Y., Leiknes, T.O. and Ghaffour, N., 2020. A Data-Driven Soft Sensor to Forecast Energy Consumption in Wastewater Treatment Plants: A Case Study. IEEE Sensors Journal, vol. 21, no. 4, pp. 4908-4917.
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Bouyeddou, B., Harrou, F. Kadri, B., and Sun, Y., 2020. Detecting network cyber-attacks using an integrated statistical approach, Cluster Computing, pp.1-19.
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Cheng, T., Harrou, F., Kadri, F., Sun, Y. and Leiknes, T., 2020. Forecasting of Wastewater Treatment Plant Key Features using Deep Learning-Based Models: A Case Study. IEEE Access, 8, pp.184475-184485.
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Harrou, F., Hittawe, M.M., Sun, Y. and Beya, O., 2020. Malicious attacks detection in crowded areas using deep learning-based approach. IEEE Instrumentation & Measurement Magazine, 23(5), pp.57-62.
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Lee, J., Wang, W., Harrou, F. and Sun, Y., 2020. Wind Power Prediction Using Ensemble Learning-Based Models. IEEE Access, 8, pp.61517-61527.
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Wang, W., Lee, J., Harrou , F. and Sun, Y., 2020. Early Detection of Parkinson’s Disease Using Deep Learning and Machine Learning. IEEE Access, 8, pp.147635-147646.
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Lee, J., Wang, W., Harrou, F., Sun, Y. (2020). Reliable solar irradiance prediction using ensemble learning-based models: A comparative study. Energy Conversion and Management, 208, 112582.
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Zeroual, A., Harrou, F., Dairi, A. and Sun, Y., 2020. Deep learning methods for forecasting COVID-19 time-Series data: A Comparative study. Chaos, Solitons & Fractals, 140, p.110121.
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Harrou, F., Khaldi, B., Sun, Y. and Cherif, F., 2020. An efficient statistical strategy to monitor a robot swarm. IEEE Sensors Journal. 20(4), pp. 1-10.
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Taghezouit, B., Harrou, F., Sun, Y., Arab, A.H. and Larbes, C., 2020. Multivariate statistical monitoring of photovoltaic plant operation. Energy Conversion and Management, 205, p.112317.
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Harrou, F., Zeroual, A. and Sun, Y., 2020. Traffic congestion monitoring using an improved kNN strategy. Measurement, Elsevier, p.107534.
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Bouyeddou, B., Kadri, B., Harrou, F. and Sun, Y., 2020. DDOS-attacks detection using an efficient measurement-based statistical mechanism. Engineering Science and Technology, an International Journal.
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Harrou, F., Kadri, F., & Sun, Y. (2020). Forecasting of Photovoltaic Solar Power Production Using LSTM Approach. In Advanced Statistical Modeling, Forecasting, and Fault Detection in Renewable Energy Systems. IntechOpen.
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Krupskii, P., Harrou, F., Hering, A.S. and Sun, Y., 2019. Copula-based monitoring schemes for non-Gaussian multivariate processes. Journal of Quality Technology, pp.1-16.
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Harrou, F., Taghezouit, B. and Sun, Y., 2019. Improved kNN-Based Monitoring Schemes for Detecting Faults in PV Systems. IEEE Journal of Photovoltaics, 9, n0. 3: 811 – 821.
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Cheng, T., Dairi, A., Harrou, F., Sun, Y. and Leiknes, T., 2019. Monitoring Influent Conditions of Wastewater Treatment Plants by Nonlinear Data-Based Techniques. IEEE Access, 7, pp.108827-108837.
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Harrou, F., Taghezouit, B. and Sun, Y., 2019. Robust and flexible strategy for fault detection in grid-connected photovoltaic systems. Energy Conversion and Management, 180, pp.1153-1166.
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Harrou, F., Dairi, A., Taghezouit, B. and Sun, Y., 2019. An unsupervised monitoring procedure for detecting anomalies in photovoltaic systems using a one-class Support Vector Machine. Solar Energy, 179, pp.48-58.
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Harrou, F., Saidi, A., & Sun, Y. (2019). Wind power prediction using bootstrap aggregating trees approach to enabling sustainable wind power integration in a smart grid. Energy Conversion and Management, 201, 112077.
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Dairi, A., Cheng, T., Harrou, F., Sun, Y. and Leiknes, T., 2019. Deep learning approach for sustainable WWTP operation: A case study on data-driven influent conditions monitoring. Sustainable Cities and Society, 50, p.101670.
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Zeroual, A., Harrou, F. and Sun, Y., 2019. Road traffic density estimation and congestion detection with a hybrid observer-based strategy. Sustainable Cities and Society, 46, p.101411.
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Khaldi, B., Harrou, F., Cherif, F. and Sun, Y., 2019. Flexible and Efficient Topological Approaches for a Reliable Robots Swarm Aggregation. IEEE Access, 7, pp.96372-96383.
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Madakyaru, M., Harrou, F. and Sun, Y., 2019. Monitoring distillation column systems using improved nonlinear partial least squares-based strategies. 19 (13), IEEE Sensors Journal.
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Harrou, F., Zerrouki, N., Sun, Y. and Houacine, A., 2019. An integrated vision-based approach for efficient human fall detection in a home environment. IEEE Access, 7, pp.114966-114974.
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Zerrouki, N., Harrou, F., Sun, Y., & Hocini, L. (2019). A Machine Learning-Based Approach for Land Cover Change Detection Using Remote Sensing and Radiometric Measurements. IEEE Sensors Journal, 19(14), 5843-5850.
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Harrou, F., Khaldi, B., Sun, Y. and Cherif, F., 2019. Monitoring robotic swarm systems under noisy conditions using an effective fault detection strategy. IEEE Sensors Journal, 19(3), pp.1141-1152.
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Cheng, T., Harrou, F., Sun, Y. and Leiknes, T., 2018. Monitoring influent measurements at water resource recovery facility using data-driven soft sensor approach. IEEE Sensors Journal, 19(1), pp.342-352.
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Harrou, F., Khaldi, B., Sun, Y. and Cherif, F., 2018. Monitoring robotic swarm systems under noisy conditions using an effective fault detection strategy. IEEE Sensors Journal, 19(3), pp.1141-1152.
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Harrou, F., Dairi, A., Sun, Y., and Senouci, M. (2018). Statistical monitoring of a wastewater treatment plant: A case study. Journal of environmental management, 223, 807-814.
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Zerrouki, N., Harrou, F., Sun, Y., and Houacine, A. (2018). Vision-based Human Action Classification Using Adaptive Boosting Algorithm. IEEE Sensors Journal, 18(12), 5115-5121.
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Zerrouki, N., Harrou, F., and Sun, Y. (2018). Statistical Monitoring of Changes to Land Cover. IEEE Geoscience and Remote Sensing Letters, 15(6), 927-931.
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Harrou, F., Dairi, A., Sun, Y., and Kadri, F. (2018). Detecting Abnormal Ozone Measurements With a Deep Learning-Based Strategy. IEEE Sensors Journal, 18(17), 7222-7232.
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Dairi, A., Harrou, F., Senouci, M., and Sun, Y. (2018). Unsupervised obstacle detection in driving environments using deep-learning-based stereovision. Robotics and Autonomous Systems, 100, 287-301.
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Harrou, F., Sun, Y., Madakyaru, M., and Bouyedou, B. (2018). An improved multivariate chart using partial least squares with continuous ranked probability score. IEEE Sensors Journal, 18(16), 6715-6726.
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Dairi, A., Harrou, F., Sun, Y., and Senouci, M. (2018). Obstacle Detection for Intelligent Transportation Systems Using Deep Stacked Autoencoder and k-Nearest Neighbor Scheme. IEEE Sensors Journal, 18(12), 5122-5132.
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Zeroual, A., Harrou, F., Sun, Y., and Messai, N. (2018). Integrating Model-Based Observer and Kullback-Leibler Metric for Estimating and Detecting Road Traffic Congestion. IEEE Sensors Journal, 18(20), 8605-8616.
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Khaldi, B., Harrou, F., Sun, Y., and Cherif, F. (2018). Self-Organization in Aggregating Robot Swarms: A DW-KNN Topological Approach, BioSystems Journal, Elsevier, 165, 106-121.
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Harrou, F., Sun, Y., Taghezouit, B., Saidi, A., and Hamlati, M. E. (2018). Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches. Renewable Energy, 116, 22-37.
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Harrou F, Zerrouki N, Sun Y, Houacine A, (2017) Vision-Based Fall Detection System for Improving Safety of Elderly People, IEEE Instrumentation & Measurement Magazine, Vol. 20, No. 6, pp. 49-56.
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Khaldi, B., Harrou, F., Cherif, F., Sun, Y. (2017). Monitoring a robot swarm using a data-driven fault detection approach. Robotics and Autonomous Systems, 97, 193-203. (KAUST Discovery Highlight)
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Harrou, F., Sun, Y. and Madakyaru, M., (2017). An Improved Wavelet‐Based Multivariable Fault Detection Scheme. In Uncertainty Quantification and Model Calibration. InTech
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Harrou, F., Madakyaru, M. and Sun, Y., (2017). Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring. Energy and Buildings, 143, pp.149-161.
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Zeroual, A., Harrou, F., Sun, Y., Messai, N. (2017). Monitoring road traffic congestion using a macroscopic traffic model and a statistical monitoring scheme. Sustainable Cities and Society, 35, 494-510.
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Garoudja, E., Harrou, F., Sun, Y., Kara, K., Chouder, A. and Silvestre. S. (2017), "Statistical fault detection in photovoltaic systems," Solar Energy, 150, 485-499.
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Madakyaru, M., Harrou, F. and Sun, Y. (2017), "Improved data-based fault detection strategy and application to distillation columns," Process Safety and Environmental Protection, 107, 22-34.
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Harrou, F., Madakyaru, M., Sun, Y., (2016). Incipient Anomaly Detection Using PCA with Multivariate Memory Monitoring Charts: Application to An Air Flow Heating System. Applied Thermal Engineering (Elsevier),109: 65-74. (KAUST Discovery Highlight)
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Harrou, F., Sun, Y. and Madakyaru, M. (2016), "Kullback-Leibler distance-based enhanced detection of incipient anomalies," Journal of Loss Prevention in the Process Industries (Elsevier), 44, 73-87.
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Harrou, F., and Sun, Y. (2016), "Statistical monitoring of linear antenna arrays," Engineering Science and Technology, an International Journal, 19, 1781-1787. (KAUST Discovery Highlight)
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Zerrouki, N., Harrou, F. Sun, Y. and Houacine, A. (2016), "Accelerometer and camera-based strategy for improved human fall detection," Journal of Medical Systems , 40: 284. (KAUST Discovery Highlight)
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Harrou, F., Madakyaru, M., Sun, Y. and Khadraoui, S. (2016), "Improved detection of incipient anomalies via multivariate memory monitoring charts: application to an air flow heating system," Applied Thermal Engineering, 109, 65-74. (KAUST Discovery Highlight)
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Harrou, F., Kadri, F., Khadraoui, S. and Sun, Y. (2016), "Ozone measurements monitoring using data-based approach," Process Safety and Environmental Protection, 100, 220-231. (KAUST Discovery Highlight)
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Harrou, F., Sun, Y. and Khadraoui, S. (2016), "Amalgamation of anomaly-detection indices for enhanced process monitoring," Journal of Loss Prevention in the Process Industries, 40, 365-377.
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Kadri, F., Harrou, F., Chaabane, S., Sun, Y. and Tahon, C. (2016), "Seasonal ARMA-based SPC charts for anomaly detection: application to emergency department systems," Neurocomputing, 173, 2102-2114.
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Harrou, F., Kadri, F., Chaabane, S., Tahon, C. and Sun, Y. (2015), "Improved principal component analysis for anomaly detection: application to an emergency department," Computers & Industrial Engineering, 88, 63-77.