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ORCIDTomasz Pelech-Pilichowski
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2020 – today
- 2024
[c15]Dawid Bialka, Malgorzata Zajecka
, Ada Brzoza-Zajecka, Tomasz Pelech-Pilichowski:
Automated Prediction of Air Pollution Conditions in Environment Monitoring Systems. ICCS (7) 2024: 223-238- 2022
- [c14]Tymoteusz Dobrzanski, Aleksandra Urbanczyk, Tomasz Pelech-Pilichowski, Marek Kisiel-Dorohinicki, Aleksander Byrski:
Neural-Network Based Adaptation of Variation Operators' Parameters for Metaheuristics. ICCS (1) 2022: 394-407 - [c13]Robert Brzoza-Woch, Tomasz Pelech-Pilichowski, Agnieszka Rudnicka, Jacek Dajda, Ewa Adamiec, Elzbieta Jarosz-Krzeminska, Marek Kisiel-Dorohinicki:
Acquisition, Storing, and Processing System for Interdisciplinary Research in Earth Sciences. ICCS (4) 2022: 422-435 - 2020
- [c12]Janusz Opila, Tomasz Pelech-Pilichowski:
Visual Analysis of Similarity and Relationships Between Legal Texts. MIPRO 2020: 1482-1487
2010 – 2019
- 2018
- [c11]Janusz Opila, Tomasz Pelech-Pilichowski:
Visualization of irregular datasets using kernel density estimation function. MIPRO 2018: 195-200 - [c10]Tomasz Pelech-Pilichowski:
On adaptive prediction of nonstationary and inconsistent large time series data. MIPRO 2018: 1260-1265 - 2017
- [c9]Jan T. Duda, Tomasz Pelech-Pilichowski:
Detection of Periodic Components from Seasonal Time Series with Moving Trend Method and Low Pass Filtering. DPS 2017: 192-202 - [c8]Janusz Opila, Tomasz Pelech-Pilichowski:
Remarks on visualization of fuzziness of cardiac data. MIPRO 2017: 283-288 - 2015
- [b1]Beata Basiura, Jerzy Duda, Bartlomiej Gawel, Janusz Opila, Tomasz Pelech-Pilichowski, Bogdan Rebiasz, Iwona Skalna:
Advances in Fuzzy Decision Making - Theory and Practice. Studies in Fuzziness and Soft Computing 333, Springer 2015, ISBN 978-3-319-26492-9, pp. 1-151 - [j1]Tomasz Pelech-Pilichowski, Jan T. Duda:
A two-level detector of short-term unique changes in time series based on a similarity method. Expert Syst. J. Knowl. Eng. 32(4): 555-561 (2015) - [p2]Tomasz Pelech-Pilichowski, Wojciech Cyrul:
Computer-Aided Legislation Based on Immune-Like Processing of Legal Texts. Logic in the Theory and Practice of Lawmaking 2015: 527-553 - [p1]Tomasz Pelech-Pilichowski, Jan T. Duda:
Low-Frequency Signal Reconstruction and Abrupt Change Detection in Non-stationary Time Series by Enhanced Moving Trend Based Filters. Advances in ICT for Business, Industry and Public Sector 2015: 111-125 - [e2]Maria Mach-Król, Celina M. Olszak, Tomasz Pelech-Pilichowski:
Advances in ICT for Business, Industry and Public Sector. Studies in Computational Intelligence 579, Springer 2015, ISBN 978-3-319-11327-2 [contents] - 2014
- [e1]Maria Mach-Król, Tomasz Pelech-Pilichowski:
Advances in Business ICT, result of the 3rd International Workshop on Advances in Business ICT, ABICT 2012, Wroclaw, Poland, September 9-12, 2012. Advances in Intelligent Systems and Computing 257, Springer 2014, ISBN 978-3-319-03676-2 [contents] - 2013
- [c7]Jan T. Duda, Tomasz Pelech-Pilichowski:
Moving Trend Based Filters Design in Frequency Domain. FedCSIS 2013: 927-930 - [c6]Jan Tadeusz Duda, Tomasz Pelech-Pilichowski:
Enhancements of Moving Trend Based Filters Aimed at Time Series Prediction. ICSS 2013: 747-756 - 2012
- [c5]Tomasz Pelech-Pilichowski, Wojciech Cyrul, Piotr Potiopa:
On Problems of Automatic Legal Texts Processing and Information Acquiring from Normative Acts. ABICT 2012: 53-67 - [c4]Tomasz Pelech-Pilichowski, Piotr Potiopa, Wojciech Cyrul:
Problems of automatic processing and analysis of information from legal texts. FedCSIS 2012: 939-943 - 2011
- [c3]Tomasz Pelech-Pilichowski:
A Hybrid Algorithm for Detecting Changes in Diagnostic Signals Received From Technical Devices. FedCSIS 2011: 321-327 - 2010
- [c2]Tomasz Pelech-Pilichowski, Jan T. Duda:
A Two-level algorithm of time series change detection based on a unique deviations similarity method. IMCSIT 2010: 259-263
2000 – 2009
- 2006
- [c1]Tomasz Pelech, Jan T. Duda:
Event Detection in Financial Time Series by Immune-Based Approach. Intelligent Information Systems 2006: 365-369
Coauthor Index
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