| Sensitivity analysis of crack propagation in pavement bituminous layered structures using a hybrid system integrating Artificial Neural Networks and Finite Element Method J Gajewski, T Sadowski Computational Materials Science 82, 114-117, 2014 | 118 | 2014 |
| Classification of wear level of mining tools with the use of fuzzy neural network J Gajewski, Ł Jedliński, J Jonak Tunnelling and underground space technology 35, 30-36, 2013 | 55 | 2013 |
| The determination of combustion engine condition and reliability using oil analysis by MLP and RBF neural networks J Gajewski, D Vališ Tribology International 115, 557-572, 2017 | 49 | 2017 |
| Geometry optimization of a thin-walled element for an air structure using hybrid system integrating artificial neural network and finite element method J Gajewski, P Golewski, T Sadowski Composite Structures 159, 589-599, 2017 | 42 | 2017 |
| Towards the identification of worn picks on cutterdrums based on torque and power signals using Artificial Neural Networks J Gajewski, J Jonak Tunnelling and Underground Space Technology 26 (1), 22-28, 2011 | 34 | 2011 |
| The effect of geometrical non-linearity on the crashworthiness of thin-walled conical energy-absorbers M Rogala, J Gajewski, M Ferdynus Materials 13 (21), 4857, 2020 | 28 | 2020 |
| Detecting and identifying non-stationary courses in the ripping head power consumption by recurrence plots G Litak, A Syta, J Gajewski, J Jonak Meccanica 45 (4), 603, 2010 | 28 | 2010 |
| Utilisation of neural networks to identify the status of the cutting tool point J Gajewski, J Jonak Tunnelling and underground space technology 21 (2), 180-184, 2006 | 28 | 2006 |
| Crashworthiness analysis of thin-walled aluminum columns filled with aluminum–silicon carbide composite foam M Rogala, J Gajewski, K Gawdzińska Composite Structures 299, 116102, 2022 | 27 | 2022 |
| Numerical simulation of brittle rock loosening during mining process J Gajewski, J Podgorski, J Jonak, Z Szkudlarek Computational Materials Science 43 (1), 115-118, 2008 | 27 | 2008 |
| Quantitative estimation of the tool wear effects in a ripping head by recurrence plots G Litak, J Gajewski, A Syta, J Jonak Journal of Theoretical and Applied Mechanics 46 (3), 521-530, 2008 | 27 | 2008 |
| Potential for using the ANN-FIS meta-model approach to assess levels of particulate contamination in oil used in mechanical systems D Vališ, J Gajewski, L Žák Tribology International 135, 324-334, 2019 | 23 | 2019 |
| Identification of ripping tool types with the use of characteristic statistical parameters of time graphs J Jonak, J Gajewski Tunnelling and Underground Space Technology 23 (1), 18-24, 2008 | 23 | 2008 |
| The use of neural networks in the analysis of dual adhesive single lap joints subjected to uniaxial tensile test J Gajewski, P Golewski, T Sadowski Materials 14 (2), 419, 2021 | 20 | 2021 |
| Verification of the technical equipment degradation method using a hybrid reinforcement learning trees–artificial neural network system J Gajewski, D Vališ Tribology International 153 (106618), 2021 | 20 | 2021 |
| Numerical analysis of the thin-walled structure with different trigger locations under axial load M Rogala, J Gajewski, M Ferdynus IOP Conference Series: Materials Science and Engineering 710 (1), 012028, 2019 | 20 | 2019 |
| Identifying the cutting tool type used in excavations using neural networks J Jonak, J Gajewski Tunnelling and underground space technology 21 (2), 185-189, 2006 | 20 | 2006 |
| Study on the effect of geometrical parameters of a hexagonal trigger on energy absorber performance using ann M Rogala, J Gajewski, M Górecki Materials 14 (20), 5981, 2021 | 16 | 2021 |
| Optimal selection of signal features in the diagnostics of mining head tools condition Ł Jedliński, J Gajewski Tunnelling and underground space technology 84, 451-460, 2019 | 15 | 2019 |
| Numerical analysis of porous materials subjected to oblique crushing force M Rogala, J Gajewski Journal of Physics: Conference Series 1736 (1), 012025, 2021 | 13 | 2021 |
Tomasz SadowskiLublin University of TechnologyVerified email at pollub.pl
