| Deep learning for financial time series forecasting in a-trader system J Korczak, M Hemes 2017 Federated Conference on Computer Science and Information Systems …, 2017 | 56 | 2017 |
| Deriving consensus for hierarchical incomplete ordered partitions and coverings. M Hernes, NT Nguyen J. Univers. Comput. Sci. 13 (2), 317-328, 2007 | 53 | 2007 |
| Deep learning for grape variety recognition B Franczyk, M Hernes, A Kozierkiewicz, A Kozina, M Pietranik, I Roemer, ... Procedia Computer Science 176, 1211-1220, 2020 | 50 | 2020 |
| Ontology of mathematical modeling based on interval data M Dyvak, A Melnyk, A Rot, M Hernes, A Pukas Complexity 2022 (1), 8062969, 2022 | 43 | 2022 |
| Application of the consensus method in a multiagent financial decision support system M Hernes, J Sobieska-Karpińska Information Systems and e-Business Management, 1-19, 2015 | 41 | 2015 |
| Digital transformation of public administration through blockchain technology A Rot, M Sobińska, M Hernes, B Franczyk Towards Industry 4.0—current challenges in information systems, 111-126, 2020 | 40 | 2020 |
| Architektura zintegrowanego systemu zarzÄ… dzania A Bytniewski, M Kowalska, M Hernes, A Chojnacka-Komorowska, ... Wydawnictwo Uniwersytetu Ekonomicznego, 2015 | 35 | 2015 |
| Risk avoiding strategy in multi-agent trading system J Korczak, M Hernes, M Bac Proceedings of Federated Conference Computer Science and Information Systems, 2013 | 32 | 2013 |
| Deep learning for customer churn prediction in e-commerce decision support M Pondel, M Wuczyński, W Gryncewicz, Ł Łysik, M Hernes, A Rot, ... Business Information Systems, 3-12, 2021 | 30 | 2021 |
| Towards Industry 4.0: Functional and technological basis for ERP 4.0 Systems A Bytniewski, K Matouk, A Rot, M Hernes, A Kozina Towards Industry 4.0—Current Challenges in Information Systems, 3-19, 2020 | 28 | 2020 |
| A cognitive integrated management support system for enterprises M Hernes Computational Collective Intelligence. Technologies and Applications: 6th …, 2014 | 27 | 2014 |
| Consensus determining algorithm in multiagent decision support system with taking into consideration improving agent's knowledge J Sobieska-Karpińska, M Hernes 2012 Federated Conference on Computer Science and Information Systems …, 2012 | 26 | 2012 |
| Food demand prediction using the nonlinear autoregressive exogenous neural network K Lutoslawski, M Hernes, J Radomska, M Hajdas, E Walaszczyk, ... IEEE Access 9, 146123-146136, 2021 | 23 | 2021 |
| Modeling Based on the Analysis of Interval Data of Atmospheric Air Pollution Processes with Nitrogen Dioxide due to the Spread of Vehicle Exhaust Gases M Dyvak, I Spivak, A Melnyk, V Manzhula, T Dyvak, A Rot, M Hernes Sustainability 15 (3), 2163, 2023 | 22 | 2023 |
| Financial time series forecasting: Comparison of traditional and spiking neural networks K Mateńczuk, A Kozina, A Markowska, K Czerniachowska, ... Procedia Computer Science 192, 5023-5029, 2021 | 20 | 2021 |
| Performance evaluation of decision-making agents’ in the multi-agent system J Korczak, M Hernes, M Bac | 19 | 2014 |
| Liquidity prediction on Vietnamese stock market using deep learning PQ Khang, M Hernes, K Kuziak, A Rot, W Gryncewicz Procedia Computer Science 176, 2050-2058, 2020 | 17 | 2020 |
| Performance evaluation of the customer relationship management agent’s in a cognitive integrated management support system M Hernes Transactions on Computational Collective Intelligence XVIII, 86-104, 2015 | 16 | 2015 |
| Deriving consensus for incomplete ordered partitions M Hernes, NT Nguyen Intelligent Technologies for Inconsistent Knowledge Processing, Advanced …, 2004 | 16 | 2004 |
| Towards Industry 4.0: Current Challenges in Information Systems M Hernes, A Rot, D Jelonek Springer, 2020 | 15 | 2020 |
Andrzej BytniewskiUniwersytet Ekonomiczny we WrocławiuVerified email at ue.wroc.pl
