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nauka:publikacje

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Publications

Total numer of publications: 70

2021 (1)
  • Marcin Blachnik, Karol Wawrzyniak, Marcin Jakubek Partitioning Power Grid for the Design of the Zonal Energy Market while Preserving Control Area Constraints. Electronics 10 (5) pp. 610. Multidisciplinary Digital Publishing Institute. 2021
2020 (3)
  • Marcin Blachnik, Joanna Henzel Estimating the Performance Indicators of Promotion Efficiency in FMCG Retail. In International Conference on Neural Information Processing. pp. 320–332. 2020
  • Mirosław Kordos, Jan Boryczko, Marcin Blachnik, Sławomir Golak Optimization of Warehouse Operations with Genetic Algorithms. Applied Sciences 10 (14) pp. 4817. Multidisciplinary Digital Publishing Institute. 2020
  • Marcin Blachnik, Mirosław Kordos Comparison of Instance Selection and Construction Methods with Various Classifiers. Applied Sciences 10 (11) pp. 3933. Multidisciplinary Digital Publishing Institute. 2020
2019 (3)
  • Marcin Blachnik Metody bazujące na prototypach w zastosowaniu do eksploracji danych. Wydaw. Politechniki Śląskiej. 2019
  • Marcin Blachnik Ensembles of Instance Selection Methods. A Comparative Study.. International Journal of Applied Mathematics and Computer Science 29 (1) Sciendo. 2019
  • Marcin Blachnik, Marek Sołtysiak, Dominika Dąbrowska Predicting presence of amphibian species using features obtained from GIS and satellite images.. ISPRS International Journal of Geo-Information 8 (3) pp. 123. MDPI. 2019
2018 (3)
  • Mirosław Kordos, łukasz Czepielik, Marcin Blachnik Data Set Partitioning in Evolutionary Instance Selection. In International Conference on Intelligent Data Engineering and Automated Learning. pp. 631–641. 2018
  • Sławomir Golak, Anna Jama, Marcin Blachnik, Tadeusz Wieczorek New Architecture of Correlated Weights Neural Network for Global Image Transformations. In International Conference on Artificial Neural Networks. pp. 56–65. 2018
  • Marcin Blachnik, Miroslaw Kordos, Slawomir Golak Data Compression Measures for Meta-Learning Systems. In 2018 Federated Conference on Computer Science and Information Systems (FedCSIS). pp. 25–28. 2018
2017 (1)
  • Marcin Blachnik Instance Selection for Classifier Performance Estimation in Meta Learning. Entropy 19 (11) pp. 583. Multidisciplinary Digital Publishing Institute. 2017
2016 (4)
  • Álvar Arnaiz-González, Marcin Blachnik, Mirosław Kordos, César García-Osorio Fusion of Instance Selection Methods in Regression Tasks. Information Fusion 30 pp. 69-79. 2016
  • Marcin Blachnik On the Relation Between kNN Accuracy and Dataset Compression Level. LNAI 9692 pp. 541–551. 2016
  • Marek Sołtysiak, Marcin Blachnik, Dominika Dąbrowska Machine learning methods in the water reservoirs classification. Environmental & Socio-economic Studies 4 2016
  • Marcin Blachnik, Mirosław Kordos Information Selection and Data Compression RapidMiner Library. In Machine Intelligence and Big Data in Industry. pp. 135–145. Springer. 2016
2015 (5)
  • Marcin Blachnik, Tadeusz Wieczorek Survey of incremental learning methods. Studia Informatica 36 (1) pp. 47–60. 2015
  • Miroslaw Kordos, Andrzej Rusiecki, Marcin Blachnik Noise reduction in regression tasks with distance, instance, attribute and density weighting. In Cybernetics (CYBCONF). pp. 73–78. IEEE Explore. 2015
  • Marcin Blachnik Reducing Time Complexity of SVM Model by LVQ Data Compression. In Artificial Intelligence and Soft Computing. pp. 687–695. Springer Verlag, LNCS 9119. 2015
  • Marcin Jakubek, Karol Wawrzyniak, Michał Kłos, Marcin Blachnik Are Locational Marginal Prices a Good Heuristic to Divide Energy Market into Bidding Zones?. In Proceedings of EEM. IEEE Explore. 2015
  • Karol Wawrzyniak, Michał Kłos, Marcin Jakubek, Marcin Blachnik, Anna Kadłubowska Nowa struktura europejskiego rynku energii-rynek strefowy. In Rynki Energii. pp. 3–6. 2015
2014 (2)
  • M. Blachnik Ensembles of Instance Selection Methods Based on Feature Subset. IEEE Procedia Computer Science 35 pp. 388–396. 2014
  • M. Blachnik, M. Kordos Bagging of Instance Selection Algorithms. LNAI 8468 pp. 40-51. 2014
2013 (3)
  • M. Blachnik, M. Kordos Instance Selection in RapidMiner. In RapidMiner: Data Mining Use Cases and Business Analytics Applications . CRC Press. 2013
  • M. Blachnik, W. Toporek Spreadsheet Link. New Extension to RapidMiner.. In Proceedings of RCoMM 2013. 2013
  • M. Kordos, M. Blachnik, S. Białka Instance Selection in Logical Rule Extraction for Regression Problems. LNAI 7895 pp. 167-175. 2013
2012 (8)
  • M. Blachnik, M. Kordos Extraction of prototype-based threshold rules using neural training procedure. LNCS 7553 pp. 255–262. 2012
  • T. Maszczyk, W. Duch, M. Blachnik Feature ranking methods used for selection of prototypes. LNCS 7553 2012
  • M. Kordos, M. Blachnik Instance Selection with Neural Networks for Regression Problems. LNCS 7553 pp. 263–270. 2012
  • M. Blachnik, M. Kordos Computational Complexity Reduction and Interpretability Improvement of Distance-based Decision Trees.. LNCS 7208 pp. 288-297. 2012
  • M. Kordos, P. Kania, P. Budzyna, M. Blachnik, T. Wieczorek, S. Golak Combining the Advantages of Neural Networks and Decision Trees for Regression Problems in a Steel Temperature Prediction System. LNCS 7209 pp. 36-45. 2012
  • M. Kordos, J. Piotrowski, S. Bialka, M. Blachnik, S. Golak, T. Wieczorek Evolutionary Optimized Forest of Regression Trees. Application in Metallurgy. LNCS 7208 pp. 409-420. 2012
  • M. Blachnik, M. Kordos, T. Wieczorek, S. Golak Selecting Representative Prototypes for Prediction the Oxygen Activity in Electric Arc Furnace. LNCS 7268 pp. 539-547. 2012
  • M. Blachnik, P. Głomb Do we need complex models for gestures? A comparison of data representation and preprocessing methods for hand gesture recognition.. LNCS 7267 pp. 477-485. 2012
2011 (7)
  • M. Blachnik, W. Duch LVQ algorithm with instance weighting for generation of prototype-based rules.. Neural Networks Elsevir. 2011
  • M. Kordos, M. Blachnik, M. Perzyk, J. Kozłowski, O. Bystrzycki, M. Gródek, A. Byrdziak, Z. Motyka A Hybrid System with Regression Trees in Steel-making Process. LNCS 6678 2011
  • M. Kordos, M. Blachnik, T. Wieczorek Temperature Prediction in Electric Arc Furnace with Neural Network Tree. LNCS 2011
  • M. Kordos, M. Blachnik, T. Wieczorek Neural Network Committees Optimized with Evolutionary Methods for Steel Temperature Control. LNCS 2011
  • M. Kordos, M.  Blachnik, T. Wieczorek Evolutionary Optimization of Regression Model Ensembles in Steel-making Process. LNCS 2011
  • M. Blachnik, M. Kordos Simplnifying SVM with Weighted LVQ Algorithm. LNCS 6936 pp. 212-219. 2011
  • M. Blachnik, M. Kordos Instance Selection and Prototype Based Rules. A new extension to RapidMiner. In Proceedings of RCoMM. 2011
2010 (8)
  • M. Blachnik, A. Bukowiec, M. Kordos, J. Biesiada Information Theory vs Correlation Based Feature Ranking Methods in Application to Metallurgical Problem Solving. LNCS 6113 pp. 289-298. 2010
  • M. Blachnik, K. Mączka, T. Wieczorek A model for temperature prediction of melted steel in the electric arc furnace(EAF). LNCS 6114 pp. 371-378. 2010
  • A. Kachel, J. Biesiada, M. Blachnik, W. Duch Infosel++: Information Based Feature Selection C++ Library. LNCS 6113 pp. 388-396. 2010
  • M. Kordos, D. Strzempa, M. Blachnik Do We Need Whatever More than k-NN?. LNCS 6113 pp. 414-421. 2010
  • T. Wieczorek, M. Blachnik, S. Golak, T. Lis Struktura funkcjonalna inteligentnego systemu ekspertowego do zarządzania produkcją stali. In Pokrokove Priemyslene Inzinierstvo, InvEnt, Słowacja 2010. 2010
  • M. Blachnik, W. Duch Improving Accuracy of LVQ Algorithm by Instance Weighting. LNCS 6354 pp. 257-266. 2010
  • M. Blachnik, T. Wieczorek, K. Mączka, G. Kopeć Identification of liquid state of scrap in Electric Arc Furnace by the use of computational intelligence methods. LNCS 6444 2010
  • M. Blachnik Inteligencja biznesowa. Przegląd metod odkrywania wiedzy i drążenia danych.. In Innowacyjne metody i narzędzia wspomagające podejmowanie decyzji w zarządzaniu. WSB Dąbrowa Górnicza. 2010
2009 (3)
  • M. Blachnik Comparison of Various Feature Selection Methods in Application to Prototype Best Rules. Advances in Intelligent and Soft Computing 57 pp. 257-264. Springer Verlag. 2009
  • M. Blachnik Czy komputery będą myśleć? Czyli dokąd zmierza sztuczna inteligencja.. Nauka i Biznes WSB Dąbrowa Górnicza. 2009
  • M. Blachnik, W. Duch, A. Kachel, J. Biesiada Feature Selection for High-Dimensional Data: A Kolmogorov-Smirnov Class Correlation-Based Filter. Recent Developments of Artificial Intelligence Methods, AI-METH Series 2009 2009
2008 (6)
  • M. Blachnik, J. Laksonen Image Classification by Histogram Features Created With Learning Vector Quantization. LNCS 5163 2008
  • M. Blachnik, W. Duch Rule Extraction from Support Vector Machines. Springer. 2008
  • M. Blachnik, W. Duch Building Localized Basis Function Networks Using Context Dependent Clustering. LNCS 5163 2008
  • T. Wieczorek, M. Blachnik, K. Maczka Building a model for time reduction of steel scrap meltdown in the electric arc furnace (EAF). General strategy with a comparison of feature selection methods.. LNCS 5097 2008
  • T. Wieczorek, M. Blachnik, K. Mączka Modelowanie procesu roztapiania złomu w piecu łukowym z wykorzystaniem sieci neuronowych i algorytmów SVM. (Modeling Steel Scrap melting process in Electric Ark Furnace using neural networks and SVM algorithm). In Informatyka w technologii metali. pp. 161-168. Wydawnictwo Naukowe Akapit, Kraków. 2008
  • T. Wieczorek, M. Blachnik Budowa inteligentnego modelu procesu roztapiania złomu w piecu łukowym z wykorzystaniem sieci neuronowo-rozmytych (Building an Intelligent Model of Steel Scrap Melting Process in the Electric Arc Furnace Using Neuro-Fuzzy Nets). Hutnik-Wiadomości Hutnicze 10 pp. 592-596. 2008
2007 (2)
  • T. Wieczorek, M. Blachnik Learning from the Internet: review of classification approaches. In Internet in the information society. pp. 72-82. WSB Dąbrowa Górnicza. 2007
  • M. Blachnik Systemy regułowe bazujące na prototypach oraz ich relacje z systemami rozmytymi w zastosowaniu do klasyfikacji danych.. 2007
2006 (3)
  • M. Blachnik, W. Duch Prototype-based threshold rules. LNCS 4234 Physica Verlag, Springer. 2006
  • M. Blachnik, W. Duch, T. Wieczorek Selection of prototypes rules – context searching via clustering. LNCS 4029 pp. 573–582. Physica Verlag, Springer. 2006
  • T. Wieczorek, M. Blachnik, W. Duch Heterogeneous distance functions for prototype rules: influence of parameters on probability estimation. International Journal of Artificial Intelligence Studies 1 pp. xxx–yyy. 2006
2005 (4)
  • T. Wieczorek, M. Blachnik, W. Duch Influence of probability estimation parameters on stability of accuracy in prototype rules using heterogeneous distance functions. Artificial Intelligence Studies 2 pp. 71-78. 2005
  • M. Blachnik, W. Duch, T. Wieczorek Probabilistic distance measures for prototype based rules. In Proc. of ICONIP. pp. 445-450. Taiwan. 2005
  • M. Blachnik, W. Duch, T. Wieczorek Threshold rules decision list. In Methods of artificial intelligence. pp. 23–24. AI-METH Series. Gliwice. 2005
  • T. Wieczorek, M. Blachnik, W. Duch Influence of probability estimation parameters on stability of accuracy in prototype rules using heterogeneous distance functions. In Proceedings of Artificial Intelligence Studies. pp. Vol.2. Siedlce. 2005
2004 (3)
  • W. Duch, M. Blachnik Fuzzy rule-based systems derived from similarity to prototypes. In LNCS. pp. 912–917. Physica Verlag, Springer. New York. 2004
  • W. Duch, T. Wieczorek, J. Biesiada, M. Blachnik Comparision of feature ranking methods based on information entropy.. In Proc. of International Joint Conference on Neural Networks. pp. 1415-1420. IEEE Press. Budapest, Hungary. 2004
  • J. Biesiada, S. Pałucha, M. Blachnik, M. Podymka Adaptacyjny system detekcji intruzów. WNT Warszawa. 2004
2002 (1)
  • M. Blachnik Warunkowe metody rozmytego grupowania w zastosowaniu do uczenia radialnych sieci neuronowych. Gliwice, Poland. 2002
nauka/publikacje.txt · Last modified: 2020/07/26 02:43 (external edit)