| Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area PS Maciąg, N Kasabov, M Kryszkiewicz, R Bembenik Environmental Modelling & Software 118, 262-280, 2019 | 59 | 2019 |
| Unsupervised anomaly detection in stream data with online evolving spiking neural networks PS Maciąg, M Kryszkiewicz, R Bembenik, JL Lobo, J Del Ser Neural Networks 139, 118-139, 2021 | 55 | 2021 |
| Effective air pollution prediction by combining time series decomposition with stacking and bagging ensembles of evolving spiking neural networks PS Maciąg, R Bembenik, A Piekarzewicz, J Del Ser, JL Lobo, ... Environmental Modelling & Software 170, 105851, 2023 | 13 | 2023 |
| Online evolving spiking neural networks for incremental air pollution prediction PS Maciąg, M Kryszkiewicz, R Bembenik 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 12 | 2020 |
| A survey on data mining methods for clustering complex spatiotemporal data PS Maciąg Beyond Databases, Architectures and Structures. Towards Efficient Solutions …, 2017 | 11 | 2017 |
| Efficient Discovery of Top-K Sequential Patterns in Event-Based Spatio-Temporal Data PS Maciag Federated Conference on Computer Science and Information Systems 2018 15, 47–56, 2018 | 8 | 2018 |
| Discovery of closed spatio-temporal sequential patterns from event data PS Maciąg, M Kryszkiewicz, R Bembenik Procedia Computer Science 159, 707-716, 2019 | 6 | 2019 |
| A comparative study of short text classification with spiking neural networks PS Maciąg, W Sitek, Ł Skonieczny, H Rybiński 2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS …, 2022 | 4 | 2022 |
| A Novel Breadth-first Strategy Algorithm for Discovering Sequential Patterns from Spatio-temporal Data PS Maciąg, R Bembenik Proceedings of the 8th International Conference on Pattern Recognition …, 2019 | 4 | 2019 |
| System monitorujący pracę bezprzewodowej sieci sensorowej oparty na przestrzennych typach danych P Dymora, M Mazurek, P Maciąg Pomiary Automatyka Kontrola 60 (10), 849-853, 2014 | 1 | 2014 |
| Unsupervised Anomaly Detection in Time Series with Evolving Spiking Neural Networks and Empirical Mode Decomposition M Paluch, PS Maciag PP-RAI 24, 2024 | | 2024 |
| Discovery of crime event sequences with constricted spatio-temporal sequential patterns PS Maciąg, R Bembenik, A Dubrawski Journal of Big Data 10 (1), 98, 2023 | | 2023 |
| Methods of sequential patterns discovery, detection of anomalies and prediction from spatio-temporal data with particular use of evolving spiking neural networks P Maciąg The Institute of Computer Science, 2022 | | 2022 |
| A Framework for Discovering Frequent Event Graphs from Uncertain Event-based Spatio-temporal Data PS Maciąg Proceedings of the 8th International Conference on Pattern Recognition …, 2019 | | 2019 |
| Efficient Discovery of Sequential Patterns from Event-Based Spatio-Temporal Data by Applying Microclustering Approach PS Maciag Intelligent Methods and Big Data in Industrial Applications, 183-199, 2019 | | 2019 |
| Effcient Discovering of Top-K Sequential Patterns in Event-Based Spatio-Temporal Data P Maciąg The Institute of Computer Science, 2017 | | 2017 |
| BUILDING AND VISUALIZING WIRELESS SENSOR NETWORKS USING SPATIAL DATATYPES P MACIAG | | 2016 |
| Methods for Clustering Spatiotemporal Data P Maciąg The Institute of Computer Science, 2016 | | 2016 |
| Building a wireless sensor network with use of RFM 12 modules-data exchange between nodes D Mazur, P Maciąg, P Kielan Measurement Automation Monitoring 61 (09), 2015 | | 2015 |
Marzena KryszkiewiczProfessor of Computer Science, Warsaw University of TechnologyVerified email at ii.pw.edu.pl
