Differential Evolution: A survey of theoretical analyses KR Opara, J Arabas Swarm and evolutionary computation 44, 546-558, 2019 | 363 | 2019 |
Comparison of mutation strategies in differential evolution–a probabilistic perspective K Opara, J Arabas Swarm and Evolutionary Computation 39, 53-69, 2018 | 94 | 2018 |
Smartphone as a monitoring tool for bipolar disorder: a systematic review including data analysis, machine learning algorithms and predictive modelling AZ Antosik-Wójcińska, M Dominiak, M Chojnacka, K Kaczmarek-Majer, ... International journal of medical informatics 138, 104131, 2020 | 51 | 2020 |
Factors affecting raveling of motorway pavements—A field experiment with new additives to the deicing brine KR Opara, M Skakuj, M Stöckner Construction and Building Materials 113, 174-187, 2016 | 21 | 2016 |
Population diversity of nonelitist evolutionary algorithms in the exploration phase J Arabas, K Opara IEEE Transactions on Evolutionary Computation 24 (6), 1050-1062, 2019 | 19 | 2019 |
Benchmarking procedures for continuous optimization algorithms K Opara, J Arabas Journal of Telecommunications and Information Technology, 73-80, 2011 | 18 | 2011 |
Control charts designed using model averaging approach for phase change detection in bipolar disorder K Kaczmarek-Majer, O Hryniewicz, KR Opara, W Radziszewska, A Olwert, ... Uncertainty Modelling in Data Science 9, 115-123, 2019 | 17 | 2019 |
Self-organizing maps using acoustic features for prediction of state change in bipolar disorder O Kamińska, K Kaczmarek-Majer, K Opara, W Jakuczun, M Dominiak, ... International Workshop on Knowledge Representation for Health Care, 148-160, 2019 | 16 | 2019 |
DMEA—an algorithm that combines differential mutation with the fitness proportionate selection J Arabas, Ł Bartnik, K Opara 2011 IEEE Symposium on Differential Evolution (SDE), 1-8, 2011 | 15 | 2011 |
Behavioral and self-reported data collected from smartphones for the assessment of depressive and manic symptoms in patients with bipolar disorder: prospective observational study M Dominiak, K Kaczmarek-Majer, AZ Antosik-Wójcińska, KR Opara, ... Journal of medical Internet research 24 (1), e28647, 2022 | 14* | 2022 |
Road roughness estimation through smartphone-measured acceleration KR Opara, K Brzeziński, M Bukowicki, K Kaczmarek-Majer IEEE Intelligent Transportation Systems Magazine 14 (2), 209-220, 2021 | 14 | 2021 |
Grammatical rhymes in Polish poetry: A quantitative analysis KR Opara Digital Scholarship in the Humanities 30 (4), 589-598, 2015 | 14 | 2015 |
Differential mutation based on population covariance matrix K Opara, J Arabas Parallel Problem Solving from Nature, PPSN XI: 11th International Conference …, 2010 | 13 | 2010 |
Computation of general correlation coefficients for interval data KR Opara, O Hryniewicz International Journal of Approximate Reasoning 73, 56-75, 2016 | 12 | 2016 |
Reverse clustering JW Owsiński, J Stańczak, K Opara, S Zadrożny, J Kacprzyk Springer International Publishing, 2021 | 10 | 2021 |
Using a reverse engineering type paradigm in clustering. An evolutionary programming based approach JW Owsiński, J Kacprzyk, K Opara, J Stańczak, S Zadrożny Fuzzy Sets, Rough Sets, Multisets and Clustering, 137-155, 2017 | 10 | 2017 |
Decomposition and metaoptimization of mutation operator in differential evolution K Opara, J Arabas International Symposium on Evolutionary Computation, 110-118, 2012 | 10 | 2012 |
Control charts based on fuzzy costs for monitoring short autocorrelated time series O Hryniewicz, K Kaczmarek-Majer, KR Opara International Journal of Approximate Reasoning 114, 166-181, 2019 | 9 | 2019 |
Differential evolution: a survey of theo-retical analyses. Swarm Evol Comput 44: 546–558 KR Opara, J Arabas | 9 | 2019 |
Efficient Calculation of Kendall’s τ for Interval Data O Hryniewicz, K Opara Synergies of Soft Computing and Statistics for Intelligent Data Analysis …, 2013 | 9 | 2013 |