| Digital twins in product lifecycle for sustainability in manufacturing and maintenance I Rojek, D Mikołajewski, E Dostatni Applied Sciences 11 (1), 31, 2020 | 84 | 2020 |
| Detection and localization of water leaks in water nets supported by an ICT system with artificial intelligence methods as a way forward for smart cities I Rojek, J Studzinski Sustainability 11 (2), 518, 2019 | 84 | 2019 |
| AI-optimized technological aspects of the material used in 3D printing processes for selected medical applications I Rojek, D Mikołajewski, E Dostatni, M Macko Materials 13 (23), 5437, 2020 | 62 | 2020 |
| Technological process planning by the use of neural networks I Rojek AI EDAM 31 (1), 1-15, 2017 | 57 | 2017 |
| Modern methods in the field of machine modelling and simulation as a research and practical issue related to Industry 4.0 I Rojek, M Macko, D Mikołajewski, M Sága, T Burczyński Bulletin of the Polish Academy of Sciences. Technical Sciences 69 (2), 2021 | 45 | 2021 |
| Intelligent system supporting technological process planning for machining and 3D printing I Rojek, D Mikołajewski, P Kotlarz, M Macko, J Kopowski Bulletin of the Polish Academy of Sciences: Technical Sciences, 2021 | 32 | 2021 |
| Hybrid artificial intelligence system in constraint based scheduling of integrated manufacturing ERP systems I Rojek, M Jagodziński Hybrid Artificial Intelligent Systems: 7th International Conference, HAIS …, 2012 | 32 | 2012 |
| Optimization of extrusion-based 3D printing process using neural networks for sustainable development I Rojek, D Mikołajewski, M Macko, Z Szczepański, E Dostatni Materials 14 (11), 2737, 2021 | 31 | 2021 |
| Ecodesign of technological processes with the use of decision trees method I Rojek, E Dostatni, A Hamrol International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain …, 2018 | 30 | 2018 |
| Neural networks as performance improvement models in intelligent CAPP systems I Rojek Control and Cybernetics 39 (1), 54-68, 2010 | 28 | 2010 |
| Comparison of different types of neuronal nets for failures location within water-supply networks I Rojek, J Studziński Eksploatacja i Niezawodność 16 (1), 42-47, 2014 | 27 | 2014 |
| An artificial intelligence approach for improving maintenance to supervise machine failures and support their repair I Rojek, M Jasiulewicz-Kaczmarek, M Piechowski, D Mikołajewski Applied Sciences 13 (8), 4971, 2023 | 26 | 2023 |
| Neural networks as prediction models for water intake in water supply system I Rojek Artificial Intelligence and Soft Computing–ICAISC 2008: 9th International …, 2008 | 26 | 2008 |
| Machine learning methods for optimal compatibility of materials in ecodesign I Rojek, E Dostatni Bulletin of the Polish Academy of Sciences. Technical Sciences 68 (2), 199-206, 2020 | 25 | 2020 |
| The use of machine learning method in concurrent ecodesign of products and technological processes E Dostatni, I Rojek, A Hamrol Advances in Manufacturing, 321-330, 2018 | 25 | 2018 |
| PREDICTIVE COMPENSATION OF THERMAL DEFORMATIONS OF BALL SCREWS IN CNC MACHINES USING NEURAL NETWORKS. I Rojek, M Kowal, A Stoic Tehnicki Vjesnik/Technical Gazette 24 (6), 2017 | 24 | 2017 |
| Hybrid neural networks as prediction models I Rojek Artifical Intelligence and Soft Computing: 10th International Conference …, 2010 | 23 | 2010 |
| Wspomaganie procesów podejmowania decyzji i sterowania w systemach o różnej skali złożoności z udziałem metod sztucznej inteligencji I Rojek-Mikołajczak Wydawnictwo Uniwersytetu Kazimierza Wielkiego, 2010 | 21 | 2010 |
| Classifier models in intelligent CAPP systems I Rojek Man-machine interactions, 311-319, 2009 | 21 | 2009 |
| Models for better environmental intelligent management within water supply systems I Rojek Water resources management 28, 3875-3890, 2014 | 19 | 2014 |
