dr hab. inż. Maciej Grzenda

MiNI PW | Strona główna | Życiorys | Zainteresowania | Publikacje | Dla studentów | Dydaktyka | Informacje | English

Wybrane publikacje

2021-

• Luckner, M., Wrona, P., Grzenda, M., Łysak, A., Analysing Urban Transport Using Synthetic Journeys. w: Franco, L., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science - ICCS 2024. ICCS 2024. Lecture Notes in Computer Science, vol 14838. Springer, Cham, 2024
• Golik, P., Grzenda, M., Sienkiewicz, E., Hybrid Ensemble-Based Travel Mode Prediction, w: Miliou, I., Piatkowski, N., Papapetrou, P. (eds) Advances in Intelligent Data Analysis XXII. IDA 2024. Lecture Notes in Computer Science, vol 14641. Springer, Cham, 2024
• Grzenda, M., Kazmierczak, S., Luckner, M., Borowik, G., Mańdziuk, J., Evaluation of machine learning methods for impostor detection in web applications, Expert Systems with Applications, vol. 231, Elsevier, 2023
• Grzenda, M., Luckner, M., Brzozowski, Ł., Quantifying Parking Difficulty with Transport and Prediction Models for Travel Mode Choice Modelling. w: Mikyska, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds), Computational Science - ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10477. Springer, Cham, 2023
• Grzenda, M., Luckner, M., Wrona, P., Urban Traveller Preference Miner: Modelling Transport Choices with Survey Data Streams w: Amini, MR., Canu, S., Fischer, A., Guns, T., Kralj Novak, P., Tsoumakas, G. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2022. Grenoble, Francja. Lecture Notes in Computer Science, vol 13718. Springer, Cham, 2023
• Wrona, P., Grzenda, M., Luckner, M., Streaming Detection of Significant Delay Changes in Public Transport Systems. w: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science. International Conference on Computational Science, Londyn, 2022. Lecture Notes in Computer Science, vol 13353. Springer, Cham, 2022
• H. Murilo Gomes, M. Grzenda, R. Mello, J. Read, M. H. Le Nguyen, A. Bifet, A Survey on Semi-Supervised Learning for Delayed Partially Labelled Data Streams, ACM Computing Surveys, 55, 4, 2022, str. 75:1-75:42
• M.Grzenda, Quantifying Changes in Predictions of Classification Models for Data Streams. w: Bouadi, T., Fromont, E., Hüllermeier, E. (eds) Advances in Intelligent Data Analysis XX. IDA 2022. Lecture Notes in Computer Science, vol 13205. Springer, Cham, 2022, str. 115-127
• M. Grzenda, J. Legierski, Towards Increased Understanding of Open Data Use for Software Development, Information Systems Frontiers, vol. 23(2), Springer, 2021, str. 495-513
• N. Kourtellis, H. Herodotou, M. Grzenda, P. Wawrzyniak, A. Bifet, S2CE: a hybrid cloud and edge orchestrator for mining exascale distributed streams, Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems, ACM, 2021, str. 103-113
• R. Kunicki, M. Grzenda, Towards Increasing Open Data Adoption Through Stream Data Integration and Imputation, IEA/AIE 2021: Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices, LNCS, vol. 12798, Springer, Cham, 2021, str. 15-27

2016-2020

• M. Grzenda, H. M. Gomes, A. Bifet, Delayed Labelling Evaluation for Data Streams. Data Mining and Knowledge Discovery, DOI: 10.1007/s10618-019-00654-y, 34, 2020, str. 1237-1266
• M. Luckner, M. Grzenda, R. Kunicki, J. Legierski, IoT Architecture for Urban Data-Centric Services and Applications, ACM Transactions on Internet Technology, 2020, vol. 20, no. 3
• M. Grzenda, H. M. Gomes and A. Bifet, Performance measures for evolving predictions under delayed labelling classification, 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, Wielka Brytania, 2020, str. 1-8, doi: 10.1109/IJCNN48605.2020.9207256.
• M. Grzenda, A. Bustillo, Semi-supervised roughness prediction with partly unlabeled vibration data streams, w: Journal of Intelligent Manufacturing, Springer, 2019, vol. 30, no. 2, str. 933-945
• M.Grzenda, Analysing the Performance of Fingerprinting-Based Indoor Positioning: The Non-trivial Case of Testing Data Selection, w: Advances and Trends in Artificial Intelligence. From Theory to Practice, LNAI, 11606, (Eds.) Wotawa, F. et al., 2019, Springer International Publishing, str. 457-469
• M. Grzenda, K. Kwasiborska, T. Zaremba, Hybrid Short Term Prediction to Address Limited Timeliness of Public Transport Data Streams, Neurocomputing, Elsevier, Vol. 391, 2020, str. 305-317
• M. Grzenda, A. Ismail Awad, J. Furtak, J. Legierski (red.), Advances in Network Systems : Architectures, Security, and Applications, Springer International Publishing, 2017
• T. Liebig, S. Peter, M. Grzenda, K. Junosza-Szaniawski, Dynamic Transfer Patterns for Fast Multi-modal Route Planning, w: Societal Geo-innovation: Selected papers of the 20th AGILE conference on Geographic Information Science, Springer International Publishing, doi: 10.1007/978-3-319-56759-4_13, 2017, str. 223-236
• M. Grzenda, K. Kwasiborska, T. Zaremba, Combining Stream Mining and Neural Networks for Short Term Delay Prediction, w: Proceedings of International Joint Conference SOCO'17-CISIS'17-ICEUTE'17 Leon, Spain, September 6-8, 2017, ed. : Perez G. et al, Springer International Publishing, doi: 10.1007/978-3-319-67180-2_18, 2018, str. 188-197
• A. Bustillo, M. Grzenda, B. Macukow, Interpreting tree-based prediction models and their data in machining processes, Integrated Computer-Aided Engineering, 2016, vol. 23, no. 4, str. 349-367

2011-2015

• D. Teixidor, M. Grzenda, A. Bustillo, J. Ciurana, Modeling pulsed laser micromachining of micro geometries using machine-learning techniques, w: Journal of Intelligent Manufacturing, 2015, Volume 26, Issue 4, str. 801-814
• S. Grabowski, M. Grzenda, J. Legierski, The Adoption of Open Data and Open API Telecommunication Functions by Software Developers, International Conference on Business Information Systems BIS 2015: Business Information Systems, Lecture Notes in Business Information Processing , 2015, str. 337-347
• M.Grzenda, Reduction of Signal Strength Data for Fingerprinting-Based Indoor Positioning, Intelligent Data Engineering and Automated Learning, IDEAL 2015, LNCS, Springer, 2015, str. 387-394
• R. Filasiak, M. Grzenda, M. Luckner, P. Zawistowski, On the Testing of Network Cyber Threat Detection Methods on Spam Example, w: Annals of telecommunications, Vol. 69, Issue 7, 2014, str. 363-377
• M. Grzenda, On the Prediction of Floor Identification Credibility in RSS-Based Positioning Techniques, w: Recent Trends in Applied Artificial Intelligence, Moonis Ali et. al. (Eds.), Lecture Notes in Computer Science, vol. 7906, Springer-Verlag, 2013, str. 610-619
• M. Grzenda, A. Bustillo, The evolutionary development of roughness prediction models, Applied Soft Computing, Elsevier, Vol. 13, Issue 5, 2013, str. 2913-2922
• M. Grzenda, A. Bustillo, G. Quintana, J. Ciurana, Improvement of surface roughness models for face milling operations through dimensionality reduction, Integrated Computer-Aided Engineering, vol. 19(2), IOS Press, 2012, str. 179-197
• M. Grzenda, Consumer-oriented heat consumption prediction, w: Control and Cybernetics, vol. 41(1), Instytut Badań Systemowych, Polska Akademia Nauk, 2012, str. 213-240
• L. Fuchs, T. Beeneken, M. Leśniewski, M. Grzenda, Korzyści ze sterowania praca systemów kanalizacji ogólnospławnej w czasie rzeczywistym, w: Gaz, woda i technika sanitarna, nr 5, 2012, str. 218-223
• M. Grzenda, Towards the Reduction of Data Used for the Classification of Network Flows, w: Hybrid Artificial Intelligent Systems, Lecture Notes in Computer Science, vol. 7209, Springer-Verlag, 2012, str. 68-77
• H. Łącka, M. Grzenda, On the Evolutionary Search for Data Reduction Method, w: Distributed Computing and Artificial Intelligence / Omatu Sigeru [i in.] ( red. ), Advances in Intelligent and Soft Computing, nr 151, 2012, str. 527-534
• M. Grzenda, Prediction-Oriented Dimensionality Reduction of Industrial Data Sets, Lecture Notes in Artificial Intelligence, vol. 6703, Springer-Verlag, Berlin, 2011, str. 233-241
• M. Grzenda, L. Fuchs, T. Beeneken, N. Wronowski, Kluczowe zagadnienia modelowania matematycznego systemów kanalizacyjnych na przykładzie dużej sieci ogólnospławnej, w: Gaz, woda i technika sanitarna, nr 3, 2011, str. 91-98
• M. Grzenda, A. Bustillo, P. Zawistowski, A Soft Computing System Using Intelligent Imputation Strategies for Roughness Prediction in Deep Drilling, Journal of Intelligent Manufacturing, Springer, vol. 23(5), (2010: DOI), 2012, str. 1733-1743

do 2010

• M. Grzenda, M. Sudoł, W. Gębski, Modelowanie systemu dystrybucji wody na przykładzie dużej aglomeracji miejskiej, w: Gaz, woda i technika sanitarna, vol. 3, 2010, str. 2-6
• P. Zawistowski, M.Grzenda, Handling Incomplete Data Using Evolution of Imputation Methods, w: Proc. of 9th International Conference ICANNGA 2009, Kuopio, Finlandia, Lecture Notes in Computer Science, vol. 5495, Springer-Verlag, Berlin, 2009, str. 22-31
• M. Grzenda, B. Macukow, Heat Consumption Prediction with Multiple Hybrid Models, w: Proc. of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Hiszpania, Lecture Notes in Computer Science, vol. 5581, Springer-Verlag, Berlin, 2009, str. 1213-1221
• M. Grzenda, Pozyskanie i przetwarzanie danych na potrzeby modelowania pracy sieci. w: Gaz, woda i technika sanitarna, vol. 6, 2009, str. 16-19
• M. Grzenda, SOM-Based Selection of Monitored Consumers for Demand Prediction, w: Proc. of 10th International Conference IDEAL 2009, Burgos, Hiszpania, Lecture Notes in Computer Science, vol. 5788, Springer-Verlag, Berlin, 2009, str. 807-814
• M. Grzenda, Load Prediction Using Combination of Neural Networks and Simple Strategies, w: Tenth Scandinavian Conference on Artificial Intelligence SCAI 2008, Sztokholm, Szwecja, Frontiers in Artificial Intelligence, vol. 173, IOS Press, 2008, str. 106-113, Amsterdam
• M. Grzenda, B. Macukow, Demand Prediction with Multi-Stage Neural Processing w: Advances in Natural Computation and Data Mining, Xidian University Press, Chiny, 2006 ISBN: 7-5606-1735-2/TP*0431, str. 131-141
• M. Grzenda, M. Niemczak, Requirements and Solutions for Web-Based Expert System, Proc. of ICAISC 2004, Zakopane, 2004, Lecture Notes in Artificial Intelligence, vol. 3070, Springer-Verlag, Berlin, str. 866-871
• M. Grzenda, B. Macukow, Evolutionary neural networks based optimization for short-term load forecasting, Control and Cybernetics, 31, no.2, 2002, str. 371-382
• B.Macukow, M.Grzenda, Towards the Evolution of Neural Networks, Optoelectronics Review, 9/3, 2001, str. 23-26
• M. Grzenda, B.Macukow, The Role of Weight Domain in Evolutionary Design of Multilayer Perceptrons, Proc. of the IEEE-INNS-ENNS International Joint Conference on Neural Networks IJCNN 2000, Los Alamitos, USA, 2000
• M. Grzenda, B. Macukow, Neural Networks to Simulate Intelligent Behaviour in the Games of Moves, Proceedings of the 13th European Simulation Multiconference, Ghent, Belgia, vol. 2, 1999, str. 429-436
• M. Grzenda, B. Macukow, Genetic Algorithm and Neural Networks to Solve the Prisoner's Dilemma, Optical Memory and Neural Networks, Allerton Press Inc., USA, vol. 7 no.3, 1998, str. 171-175