A method for resampling imbalanced datasets in binary classification tasks for real-world problems S Cateni, V Colla, M Vannucci Neurocomputing 135, 32-41, 2014 | 209 | 2014 |
Reducing the energy consumption and CO2 emissions of energy intensive industries through decision support systems–An example of application to the steel industry GF Porzio, B Fornai, A Amato, N Matarese, M Vannucci, L Chiappelli, ... Applied energy 112, 818-833, 2013 | 133 | 2013 |
Variable selection and feature extraction through artificial intelligence techniques S Cateni, M Vannucci, M Vannocci, V Colla Multivariate analysis in management, engineering and the Science 6, 103-118, 2012 | 77 | 2012 |
Outlier detection methods for industrial applications S Cateni, V Colla, M Vannucci, J Aramburo, AR Trevino Advances in Robotics, Automation and Control, 265-282, 2008 | 71 | 2008 |
Meaningful discretization of continuous features for association rules mining by means of a SOM. M Vannucci, V Colla ESANN, 489-494, 2004 | 63 | 2004 |
Comparison of multi-objective optimization techniques applied to off-gas management within an integrated steelwork GF Porzio, G Nastasi, V Colla, M Vannucci, TA Branca Applied Energy 136, 1085-1097, 2014 | 60 | 2014 |
Process integration in energy and carbon intensive industries: An example of exploitation of optimization techniques and decision support GF Porzio, V Colla, N Matarese, G Nastasi, TA Branca, A Amato, B Fornai, ... Applied Thermal Engineering 70 (2), 1148-1155, 2014 | 56 | 2014 |
A hybrid feature selection method for classification purposes S Cateni, V Colla, M Vannucci 2014 European Modelling Symposium, 39-44, 2014 | 55 | 2014 |
A fuzzy inference system applied to defect detection in flat steel production A Borselli, V Colla, M Vannucci, M Veroli International Conference on Fuzzy Systems, 1-6, 2010 | 55 | 2010 |
Novel classification method for sensitive problems and uneven datasets based on neural networks and fuzzy logic M Vannucci, V Colla Applied Soft Computing 11 (2), 2383-2390, 2011 | 49 | 2011 |
A fuzzy logic-based method for outliers detection. S Cateni, V Colla, M Vannucci Artificial Intelligence and Applications, 605-610, 2007 | 47 | 2007 |
A genetic algorithm-based approach for selecting input variables and setting relevant network parameters of a SOM-based classifier S Cateni, V Colla, M Vannucci Int. J. Simul. Syst. Sci. Technol 12 (2), 30-37, 2011 | 45 | 2011 |
Process integration analysis and some economic-environmental implications for an innovative environmentally friendly recovery and pre-treatment of steel scrap GF Porzio, V Colla, B Fornai, M Vannucci, M Larsson, H Stripple Applied Energy 161, 656-672, 2016 | 44 | 2016 |
Variable selection through genetic algorithms for classification purposes S Cateni, V Colla, M Vannucci Proceedings of the 10th IASTED International Conference on Artificial …, 2010 | 43 | 2010 |
General purpose input variables extraction: A genetic algorithm based procedure GIVE a GAP S Cateni, V Colla, M Vannucci 2009 Ninth International Conference on Intelligent Systems Design and …, 2009 | 41 | 2009 |
A fuzzy system for combining filter features selection methods S Cateni, V Colla, M Vannucci International Journal of Fuzzy Systems 19, 1168-1180, 2017 | 40 | 2017 |
Thresholded neural networks for sensitive industrial classification tasks M Vannucci, V Colla, M Sgarbi, O Toscanelli Bio-Inspired Systems: Computational and Ambient Intelligence: 10th …, 2009 | 32 | 2009 |
Flatness defect detection and classification in hot rolled steel strips using convolutional neural networks M Vannocci, A Ritacco, A Castellano, F Galli, M Vannucci, V Iannino, ... Advances in Computational Intelligence: 15th International Work-Conference …, 2019 | 29 | 2019 |
A fuzzy system for combining different outliers detection methods S Cateni, V Colla, M Vannucci Proceedings of the IASTED International Conference on Artificial …, 2009 | 26 | 2009 |
Prediction of hot deformation resistance during processing of microalloyed steels in plate rolling process A Dimatteo, M Vannucci, V Colla The International Journal of Advanced Manufacturing Technology 66, 1511-1521, 2013 | 23 | 2013 |