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nauka:publikacje

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Publications

Total numer of publications: 65

2019 (2)
  • 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)
  • Miros{ l}aw Kordos, { L}ukasz Czepielik, Marcin Blachnik Data Set Partitioning in Evolutionary Instance Selection. In International Conference on Intelligent Data Engineering and Automated Learning. pp. 631–641. 2018
  • S{ l}awomir 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, Miros{ l}aw 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
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nauka/publikacje.txt · Last modified: 2019/03/21 13:06 (external edit)