Publications

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Articles dans revues internationales à comité de lecture

- MC. Sorkun, ÖD. İncel, C. Paoli, Time series forecasting on multivariate solar radiation data using deep learning (LSTM), Turkish Journal of Electrical Engineering & Computer Sciences 28 (1), 211-223, (IF2018 0,625; IF5 ans 0,708), 2020. https://doi.org/10.3906/elk-1907-218 

- A. Fouilloy, C. Voyant, G. Notton, F. Motte, C. Paoli, ML. Nivet, E Guillot, Solar irradiation prediction with machine learning: Forecasting models selection method depending on weather variability, Energy 165, 620-629, (IF2017 4,968; IF5 ans 5,582, HIndex:60), 2018.https://doi.org/10.1016/j.energy.2018.09.116 

- G. Notton, ML. Nivet, C. Voyant, C. Paoli, C. Darras, F. Motte, A. Fouilloy, Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting, Renewable and Sustainable Energy Reviews 87, 96-105, (IF2017 9,184; IF5 ans 10,093, HIndex:193), 2018. https://doi.org/10.1016/j.rser.2018.02.007 

- C. Voyant, G. Notton, S. Kalogirou, ML. Nivet, C. Paoli, F. Motte, A. Fouilloy, Machine learning methods for solar radiation forecasting: A review, Renewable Energy 105, 569-582, 41 (IF2016 4,357; IF5 ans 4,825, Hindex:60), 2017. https://doi.org/10.1016/j.renene.2016.12.095 

- C. Voyant, F. Motte, A. Fouilloy, G. Notton, C. Paoli, ML. Nivet, Forecasting method for global radiation time series without training phase: Comparison with other well-known prediction methodologies, Energy 120, 199-208, 3, 2017 (IF2016 4,520; IF5 ans 5,182, HIndex:60). https://doi.org/10.1016/j.energy.2016.12.118 

- C. Voyant, G. Notton, C. Darras, A. Fouilloy, F. Motte, C. Paoli, Uncertainties in global radiation time series forecasting using machine learning: The multilayer perceptron case, Energy 125, 248-257, (IF2016 4,520; IF5 ans 5,182, HIndex:60), 2017. https://doi.org/10.1016/j.energy.2017.02.098 

- K. Dahmani, G. Notton, C. Voyant, R. Dizene, ML. Nivet, C. Paoli, W. Tamas, Multilayer Perceptron approach for estimating 5-min and hourly horizontal global irradiation from exogenous meteorological data in locations without solar measurements, Renewable Energy 90, 267-282 (IF2016 4,357; IF5 ans 4,825, Hindex:60), 2016. https://doi.org/10.1016/j.renene.2016.01.013 

- W. Tamas, G. Notton, C. Paoli, M-L. Nivet, C..Voyant, « Hybridization of Air Quality Forecasting Models Using Machine Learning and Clustering: An Original Approach to Detect Pollutant Peaks », Aerosol and Air Quality Research, 16 (2), 405-416 (IF2014 2,094, IF5 ans 2.16, HIndex:23), 2016. https://doi.org/10.4209/aaqr.2015.03.0193  

- K. Dahmani, R. Dizene, G. Notton, C. Paoli, C. Voyant, M-L. Nivet, « Estimation of 5-min time-step data of tilted solar global irradiation using ANN (Artificial Neural Network) model », Energy, Volume 70, Pages 374-381, June 2014 (IF2016 4,520; IF5 ans 5,182, HIndex:60). http://dx.doi.org/10.1016/j.energy.2014.04.011 

- C. Voyant, P. Haurant, M. Muselli, C. Paoli, M-L. Nivet, « Time series modeling and large scale global solar radiation forecasting from geostationary satellites data » Solar Energy, Volume 102, Pages 131-142, 2014 (IF2016 4.018; IF5 ans 4,739, HIndex:72). http://dx.doi.org/10.1016/j.solener.2014.01.017 

- C. Voyant, C. Darras, M. Muselli, C. Paoli, M-L. Nivet, P. Poggi, « Bayesian rules and stochastic models for high accuracy prediction of solar radiation », Applied Energy 114, 218-226, 2014 (IF2016 7,182; IF5 ans 7,500, HIndex:53). http://dx.doi.org/10.1016/j.apenergy.2013.09.051  

- C. Voyant, C. Paoli, M. Muselli, M-L. Nivet, « Multi-horizon solar radiation forecasting for Mediterranean locations using time series models », Renewable and Sustainable Energy Reviews 28, 44-52, 2013 (IF2016 8,050; IF5 ans 9,122, Hindex:77). http://dx.doi.org/10.1016/j.rser.2013.07.058 

- C. Voyant, P. Randimbivololona, M-L. Nivet, C. Paoli, M. Muselli, « 24-hours ahead global irradiation forecasting using Multi-Layer Perceptron », Meteorological Applications, 2013 (IF2016 1,411 Hindex:26). http://10.1002/met.1387. 

- C. Voyant, M. Muselli, C. Paoli, M-L. Nivet, « Hybrid methodology for hourly global radiation forecasting in Mediterranean area », Renewable Energy, Volume 53, May 2013, Pages 1-11 (IF2016 4,357; IF5 ans 4,825, Hindex:60). http://dx.doi.org/10.1016/j.renene.2012.10.049 

- G. Notton, C. Paoli, L. Ivanova, S. Vasileva, M-L. Nivet, « Neural network approach to estimate 10-min solar global irradiation values on tilted planes », Renewable Energy, Volume 50, Pages 576-584, February 2013 (IF2016 4,357; IF5 ans 4,825, Hindex:60). http://dx.doi.org/10.1016/j.renene.2012.07.035  

- G. Notton, C. Paoli, M-L. Nivet, S. Vasileva, J-L Canaletti, C. Cristofari, « Estimation of hourly solar global irradiations on tilted planes from horizontal ones using artificial neural », Energy, Volume 39, Issue 1, Pages 166-179, March 2012 (IF2016 4,520; IF5 ans 5,182, HIndex:60). http://dx.doi.org/10.1016/j.energy.2012.01.038 

- C. Voyant, M. Muselli, C. Paoli, M-L. Nivet, « Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation », Energy, Volume 39, Issue 1, Pages 341-355, March 2012 (IF2016 4,520; IF5 ans 5,182, HIndex:60). http://dx.doi.org/10.1016/j.energy.2012.01.006 

- C. Voyant, M. Muselli, C. Paoli, M-L. Nivet, « Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation », Energy, Volume 36, Issue 1, Pages 348-359, January 2011 (IF2016 4,520; IF5 ans 5,182, HIndex:60). http://dx.doi.org/10.1016/j.energy.2010.10.032 

- C. Paoli, C. Voyant, M. Muselli, M-L. Nivet, « Forecasting of preprocessed daily solar radiation time series using neural networks », Solar Energy, vol. 84, n°. 12, p. 2146-2160, December 2010 (IF2016 4.018; IF5 ans 4,739, HIndex:72). http://dx.doi.org/10.1016/j.solener.2010.08.011 

Articles dans revues nationales à comité de lecture 

- C. Voyant, C. Paoli, ML. Nivet, G. Notton, A. Fouilloy, F. Motte, “Multi-layer Perceptron and Pruning”, Turkish Journal of Forecasting 1 (1), 1-8, 2017

- I. Caluianu, G. Notton, I. Colda, C. Paoli, Maximum power point prediction of a PV module using artificial neural networks. Sesiunea de comunicari stiintifice a scolii doctorale din universitatea tehnica de constructii bucuresti 23, pp. 51-58, 23ISBN: 978-973-100-129-6, editure conspress, 2010. 

- I. Caluianu, G. Notton, I. Colda, C. Paoli, « Photovoltaic Module Maximum Power Point using One Diode Model and an Artificial Neural Network Model », Mathematical Modelling in Civil Engineering, n°1-2, pp. 33-38. ISSN 2066-6926, Mars 2011.

Chapitres d’ouvrages

- G. Notton, K. Dahmani, R. Dizene, M-L. Nivet, C. Voyant, C. Paoli, Application of ANN Methods for Solar Radiation Estimation, January 2016, In book: Artificial Neural Networks: New ResearchChapter: 5Publisher: Nova. 

- P. Oberti, C. Paoli, « Participative and multicriteria localization of wind farm projects in Corsica island: decision aid process and results », Springer Berlin Heidelberg, Evaluation and Decision Models with Multiple Criteria, 2015. 

Ouvrages individuels et direction d’ouvrages collectifs 

- G. Notton, C. Paoli, M-L. Nivet, C. Voyant, « Prédire le vent et le soleil en s’inspirant du fonctionnement du cerveau », numéro spécial Energie, Stantari, 2013.

Actes publiés de conférences internationales, congrès et colloques…

- MC. Sorkun, C. Paoli, O. Durmaz Incel, “Time Series Forecasting on Solar Irradiation using Deep Learning”, 10th International Conference on Electrical and Electronics Engineering, ELECO, December 2017. 

- A. Fouilloy, C. Voyant, G. Notton, ML. Nivet, F. Motte, JL. Duchaud, C. Paoli, “Global irradiation interval forecasts based on artificial neural network”, 1st International web conference on forecasting, 2017. 

- C. Voyant, F. Motte, A. Fouilloy, G. Notton, C. Paoli, ML. Nivet , “Kalman filtering and classical time series tools for global radiation prediction”, 4th International Conference on Energy, Sustainability and Climate Change, IRCC, 2017.

- C. Voyant, G. Notton, ML. Nivet, F. Motte, A .Fouilloy, C. Paoli, “Bounded global irradiation prediction based on multilayer perceptron and time series formalism”, Electrical Machines, Drives and Power Systems (ELMA) 15th, 2017.

- C. Voyant, C. Join, M. Fliess, M-L. Nivet, M. Muselli, C. Paoli, « On meteorological forecasts for energy management and large historical data: A first look », International Conference on Renewable Energies and Power Quality (ICREPQ'15), 2015. 

- C. Voyant, M-L. Nivet, C. Paoli, M. Muselli, G. Notton, « Meteorological time series forecasting based on MLP modelling using heterogeneous transfer functions », International Conference on Mathematical Modeling in Physical Sciences 2014, Madrid : Spain (2014). 

- G. Notton, C. Paoli, S. Diaf, « Estimation of Tilted Solar Irradiation Using Artificial Neural Networks », Mediterranean Green Energy Forum 2013: Proceedings of an International Conference MGEF-13, Volume 42, Pages 33–42, 2013. http://dx.doi.org/10.1016/j.egypro.2013.11.003 

- P. Haurant, C. Voyant, M. Muselli, M-L. Nivet, C. Paoli, « Hourly global radiation prediction from geostationary satellite datahourly global radiation prediction from geostationary satellite data », International Conférence EU PVSEC, 2013. 

- C. Voyant, D. Kahina, G. Notton, C. Paoli, M-L. Nivet, M. Muselli, P Haurant, « The global radiation forecasting based on NWP or stochastic modeling: an objective criterion of choice », International Conference ICNCRE, 2013.

- K. Dahmani, G. Notton, R. Dizene, C. Paoli, C. Voyant, M-L. Nivet, K Karouk, « Estimation of 5-min solar global irradiation on tilted planes by ANN method in Bouzareah », International Conference ICNCRE, 2013.

- C. Voyant, W. Tamas, C. Paoli, A. Balu, M. Muselli, M-L. Nivet, G. Notton, « Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method », International Conference IC-MSQUARE, 2013.

- C. Paoli, C. Voyant, M. Muselli, M-L. Nivet, « Multi-horizon Irradiation Forecasting Using Time Series Models » International Conference ISES Solar World Congress, 2013.

- W. Tamas, G. Notton, C. Paoli, C. Voyant, M-L. Nivet, A Balu, « Urban ozone concentration forecasting with artificial neural network in Corsica », International Conference EENVIRO, 2013.

- C. Paoli, G. Notton, M-L. Nivet, M. Padovani, J-L. Savelli, « Neural Network Model Forecasting for Prediction of Hourly Ozone Concentration in Corsica », 10th IEEE International Conference on Environment and Electrical Engineering, Roma, Italy, 2011.

- C. Paoli, C. Voyant, M. Muselli, M-L. Nivet, « Use of exogenous data to improve an artificial neural networks dedicated to daily global radiation forecasting », 9th IEEE International Conference on Environment and Electrical Engineering, Prague, Czech Republic, May 2010. 

- C. Paoli, C. Voyant, M. Muselli, M-L. Nivet, « Solar Radiation Forecasting Using Ad-Hoc Time Series Preprocessing and Neural Network », 5th IEEE International Conference on Intelligent Computing (ICIC) Ulsan: Korea, p. 898-907, 2009. 

- C. Paoli, M-L. Nivet, J-F. Santucci, « Use of constraint solving in order to generate test vectors for behavioral validation, communication », IEEE International High Level Design Validation and Test Workshop (HLDVT'00), Berkeley, California, USA, pp. 15-20, 8-10 November 2000. 

- J-F. Santucci, C. Paoli, « High level test bench generation using software engineering concepts », 30th IEEE International Test Conference (ITC’99), Atlantic City, New Jersey, USA, 28-30 September 1999.  

- C. Paoli, J-F. Santucci, « Validation of Behavioral VHDL Descriptions Using Software Engineering Concepts », 2nd IEEE Electronic Circuits and Systems Conference (ECS’99), Bratislava, Slovakia, pp. 215-218, 6-8 September 1999. 

Workshops/ateliers internationaux avec comité de lecture

- C. Paoli, M-L Nivet, F. Bernardi, L. Capocchi, « Simulation-Based Validation of VHDL Description Using Constraints Logic Programming », IEEE International 5th Workshop on RTL and High Level Testing, Osaka, Japan, 11-12 November 2004. 

- C. Paoli, M-L. Nivet, J-F. Santucci, T. Campana, « Path-Oriented Test Data Generation of Behavioral VHDL Description », IEEE International Workshop on Electronic Design, Test & Applications (DELTA'02), Christchurch, New Zealand, pp. 382-386, 29-31 November 2002.

- C. Paoli, M-L. Nivet, J.F. Santucci, « Test Vectors Generation using Path Selection and Constraint Solving for the Validation of Behavioral VHDL Design », 4th IEEE International Workshop on System Test and Diagnosis workshop (IWSTD’00), Atlantic City, New Jersey, USA, 5 p, 5-6 October 2000.  

- C. Paoli, J-F. Santucci, « High Level Test Benches Generation for the Validation of VHDL Models of Microelectronic Systems », communication, 3rd IEEE International Workshop on System Test and Diagnosis workshop (IWSTD’99), Atlantic City, New Jersey, USA, 4 p, 30 September - 1 October 1999. 

Séminaires invités

- 2017 : Atelier de recherche du Centre de Civilisation et d’Etudes Francophones de l’Université de Varsovie – le futur des compétences – les compétences du futur – Economie et société du XXIème siècle. 

Brevets, licences, logiciels 

- De 2013 à 2017 : Développement d’un logiciel de visualisation et de traitement de données multi-sources liée à la prédiction de pics de pollution pour le compte de l'association agréée Qualitair Corse. 

- De 2008 à 2017 : Développement d’un prototype logiciel monoposte mono-utilisateur dans le cadre du projet MECADEPPE (MEdiation des Connaissances d'Acteurs Destinée à L'Evaluation des Projets et Politiques d'Energie). 

- De 2005 à 2011 : Participation à l’évolution du système de gestion de contenu (CMS en anglais pour "Content Management System") développé par la société WMaker. 

- En 2007 : Développement du prototype logiciel Xfruits, http://www.xfruits.com : Outil collaboratif de veille et de publication. 

- En 2006 : Mise en place d’un partenariat entre Microsoft et la Collectivité Territoriale de Corse (CTC) pour la traduction en langue corse de la suite bureautique Office. 

- De 2001 à 2004 : Développement du prototype logiciel GENESI (GENErateur de StimulI) permettant de générer des stimuli à partir d’une description VHDL comportementale au niveau algorithmique.