Application of rule induction algorithms for analysis of data collected by seismic hazard monitoring systems in coal mines M Sikora Archives of Mining Sciences 55 (1), 91-114, 2010 | 83 | 2010 |
A framework for learning and embedding multi-sensor forecasting models into a decision support system: A case study of methane concentration in coal mines D Ślęzak, M Grzegorowski, A Janusz, M Kozielski, SH Nguyen, M Sikora, ... Information Sciences 451, 112-133, 2018 | 74 | 2018 |
Predicting seismic events in coal mines based on underground sensor measurements A Janusz, M Grzegorowski, M Michalak, Ł Wróbel, M Sikora, D Ślęzak Engineering Applications of Artificial Intelligence 64, 83-94, 2017 | 48 | 2017 |
GuideR: A guided separate-and-conquer rule learning in classification, regression, and survival settings M Sikora, Ł Wróbel, A Gudyś Knowledge-Based Systems 173, 1-14, 2019 | 47 | 2019 |
Rule quality measures settings in classification, regression and survival rule induction—an empirical approach Ł Wróbel, M Sikora, M Michalak Fundamenta Informaticae 149 (4), 419-449, 2016 | 39 | 2016 |
Application of rule-based models for seismic hazard prediction in coal mines J Kabiesz, B Sikora, M Sikora, Ł Wróbel Acta Montanistica Slovaca, 262-277, 2013 | 38 | 2013 |
Energy consumption forecasting for the digital-twin model of the building J Henzel, Ł Wróbel, M Fice, M Sikora Energies 15 (12), 4318, 2022 | 35 | 2022 |
Data-driven adaptive selection of rule quality measures for improving rule induction and filtration algorithms M Sikora, Ł Wróbel International Journal of General Systems 42 (6), 594-613, 2013 | 34 | 2013 |
RuleKit: A comprehensive suite for rule-based learning A Gudyś, M Sikora, Ł Wróbel Knowledge-Based Systems 194, 105480, 2020 | 29 | 2020 |
Mining data from coal mines: IJCRS’15 data challenge A Janusz, M Sikora, Ł Wróbel, S Stawicki, M Grzegorowski, P Wojtas, ... Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 15th …, 2015 | 29 | 2015 |
Data-driven adaptive selection of rules quality measures for improving the rules induction algorithm M Sikora, Ł Wróbel Rough Sets, Fuzzy Sets, Data Mining and Granular Computing: 13th …, 2011 | 28 | 2011 |
RuleXAI—A package for rule-based explanations of machine learning model D Macha, M Kozielski, Ł Wróbel, M Sikora SoftwareX 20, 101209, 2022 | 27 | 2022 |
DISESOR-decision support system for mining industry M Kozielski, M Sikora, Ł Wróbel 2015 Federated Conference on Computer Science and Information Systems …, 2015 | 26 | 2015 |
Learning rule sets from survival data Ł Wróbel, A Gudyś, M Sikora BMC bioinformatics 18, 1-13, 2017 | 24 | 2017 |
Sensor-based predictive maintenance with reduction of false alarms—A case study in heavy industry M Hermansa, M Kozielski, M Michalak, K Szczyrba, Ł Wróbel, M Sikora Sensors 22 (1), 226, 2021 | 20 | 2021 |
Regression rule learning for methane forecasting in coal mines M Kozielski, A Skowron, Ł Wróbel, M Sikora Beyond Databases, Architectures and Structures: 11th International …, 2015 | 20 | 2015 |
Predicting Dangerous Seismic Events: AAIA'16 Data Mining Challenge A Janusz, D Ślęzak, M Sikora, Ł Wróbel 2016 Federated Conference on Computer Science and Information Systems …, 2016 | 19 | 2016 |
Influence of outliers introduction on predictive models quality M Kalisch, M Michalak, M Sikora, Ł Wróbel, P Przystałka Beyond Databases, Architectures and Structures. Advanced Technologies for …, 2016 | 17 | 2016 |
SCARI: Separate and conquer algorithm for action rules and recommendations induction M Sikora, P Matyszok, Ł Wróbel Information Sciences 607, 849-868, 2022 | 15 | 2022 |
Monitoring and maintenance of a gantry based on a wireless system for measurement and analysis of the vibration level M SikorA, K Szczyrba, Ł Wróbel, M Michalak Eksploatacja i Niezawodność 21 (2), 341-350, 2019 | 15 | 2019 |