HuntMi: an efficient and taxon-specific approach in pre-miRNA identification A Gudyś, MW Szcześniak, M Sikora, I Makałowska BMC bioinformatics 14, 1-10, 2013 | 88 | 2013 |
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 | 82 | 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 | 71 | 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 |
Induction and pruning of classification rules for prediction of microseismic hazards in coal mines M Sikora Expert Systems with Applications 38 (6), 6748-6758, 2011 | 46 | 2011 |
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 | 43 | 2019 |
Application of rule-based models for seismic hazard prediction in coal mines. J Kabiesz, B Sikora, M Sikora, Ł Wróbel Acta Montanistica Slovaca 18 (4), 2013 | 38 | 2013 |
Rule quality measures in creation and reduction of data rule models M Sikora International Conference on Rough Sets and Current Trends in Computing, 716-725, 2006 | 38 | 2006 |
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 | 37 | 2016 |
Decision rule-based data models using TRS and NetTRS–methods and algorithms M Sikora Transactions on Rough Sets XI, 130-160, 2010 | 36 | 2010 |
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 | 33 | 2013 |
Application of machine learning for prediction a methane concentration in a coal-mine M Sikora, B Sikora Archives of Mining Sciences 51 (4), 475-492, 2006 | 30 | 2006 |
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 |
Energy consumption forecasting for the digital-twin model of the building J Henzel, Ł Wróbel, M Fice, M Sikora Energies 15 (12), 4318, 2022 | 27 | 2022 |
RuleKit: A comprehensive suite for rule-based learning A Gudyś, M Sikora, Ł Wróbel Knowledge-Based Systems 194, 105480, 2020 | 26 | 2020 |
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 | 22 | 2017 |
Improving prediction models applied in systems monitoring natural hazards and machinery M Sikora, B Sikora International Journal of Applied Mathematics and Computer Science 22 (2 …, 2012 | 22 | 2012 |
Application of a hybrid method of machine learning for description and on-line estimation of methane hazard in mine workings M Sikora, Z Krzystanek, B Bojko, K Śpiechowicz Journal of Mining Science 47, 493-505, 2011 | 22 | 2011 |