T. Pamuła

765 total citations
21 papers, 520 citations indexed

About

T. Pamuła is a scholar working on Building and Construction, Automotive Engineering and Control and Systems Engineering. According to data from OpenAlex, T. Pamuła has authored 21 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Building and Construction, 7 papers in Automotive Engineering and 5 papers in Control and Systems Engineering. Recurrent topics in T. Pamuła's work include Traffic Prediction and Management Techniques (9 papers), Transportation Planning and Optimization (5 papers) and Traffic control and management (4 papers). T. Pamuła is often cited by papers focused on Traffic Prediction and Management Techniques (9 papers), Transportation Planning and Optimization (5 papers) and Traffic control and management (4 papers). T. Pamuła collaborates with scholars based in Poland. T. Pamuła's co-authors include Piotr Nowakowski, Renata Żochowska, Marcin Bernaś, Piotr Porwik, Bartłomiej Płaczek and Aleksander Król and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Waste Management.

In The Last Decade

T. Pamuła

18 papers receiving 491 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
T. Pamuła Poland	10	203	129	127	122	119	21	520
Akmal Abdelfatah United Arab Emirates	14	866 4.3×	81 0.6×	96 0.8×	211 1.7×	72 0.6×	59	1.2k
Davide Anghinolfi Italy	11	101 0.5×	51 0.4×	34 0.3×	35 0.3×	49 0.4×	22	541
Luís Santos Portugal	8	95 0.5×	25 0.2×	72 0.6×	105 0.9×	23 0.2×	15	504
Insung Hong South Korea	9	143 0.7×	62 0.5×	19 0.1×	14 0.1×	375 3.2×	15	595
Seunghyeon Lee South Korea	14	243 1.2×	20 0.2×	139 1.1×	247 2.0×	60 0.5×	45	590
Michael Baumann Germany	11	72 0.4×	35 0.3×	415 3.3×	25 0.2×	270 2.3×	26	583
Ali Payıdar Akgüngör Türkiye	12	171 0.8×	6 0.0×	59 0.5×	111 0.9×	57 0.5×	40	404
Soomin Woo South Korea	8	130 0.6×	11 0.1×	126 1.0×	95 0.8×	94 0.8×	30	345
Keshuang Tang China	20	544 2.7×	6 0.0×	278 2.2×	378 3.1×	68 0.6×	87	959
İlker Küçükoğlu Türkiye	11	121 0.6×	18 0.1×	221 1.7×	21 0.2×	152 1.3×	20	558

Countries citing papers authored by T. Pamuła

Since Specialization

Citations

This map shows the geographic impact of T. Pamuła's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by T. Pamuła with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Pamuła more than expected).

Fields of papers citing papers by T. Pamuła

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. Pamuła. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by T. Pamuła. The network helps show where T. Pamuła may publish in the future.

Co-authorship network of co-authors of T. Pamuła

This figure shows the co-authorship network connecting the top 25 collaborators of T. Pamuła. A scholar is included among the top collaborators of T. Pamuła based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with T. Pamuła. T. Pamuła is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Żochowska, Renata & T. Pamuła. (2024). Impact of Traffic Flow Rate on the Accuracy of Short-Term Prediction of Origin-Destination Matrix in Urban Transportation Networks. Remote Sensing. 16(7). 1202–1202. 4 indexed citations

Pamuła, T., et al.. (2022). Prediction of Electric Buses Energy Consumption from Trip Parameters Using Deep Learning. Energies. 15(5). 1747–1747. 24 indexed citations

Pamuła, T. & Renata Żochowska. (2022). Estimation and prediction of the OD matrix in uncongested urban road network based on traffic flows using deep learning. Engineering Applications of Artificial Intelligence. 117. 105550–105550. 31 indexed citations

Pamuła, T., et al.. (2021). Detection of Safe Passage for Trains at Rail Level Crossings Using Deep Learning. Sensors. 21(18). 6281–6281. 5 indexed citations

Nowakowski, Piotr & T. Pamuła. (2020). Application of deep learning object classifier to improve e-waste collection planning. Waste Management. 109. 1–9. 172 indexed citations

Pamuła, T., et al.. (2020). Estimation of the Energy Consumption of Battery Electric Buses for Public Transport Networks Using Real-World Data and Deep Learning. Energies. 13(9). 2340–2340. 85 indexed citations

Pamuła, T.. (2018). Impact of Data Loss for Prediction of Traffic Flow on an Urban Road Using Neural Networks. IEEE Transactions on Intelligent Transportation Systems. 20(3). 1000–1009. 54 indexed citations

Pamuła, T.. (2018). Road Traffic Conditions Classification Based on Multilevel Filtering of Image Content Using Convolutional Neural Networks. IEEE Intelligent Transportation Systems Magazine. 10(3). 11–21. 41 indexed citations

Pamuła, T.. (2016). Neural Networks in Transportation Research-Recent Applications. Transport Problems. 11(2). 7 indexed citations

10.

Pamuła, T.. (2016). NEURAL NETWORKS IN TRANSPORTATION RESEARCH – RECENT APPLICATIONS. Transport Problems. 11(2). 27–36. 10 indexed citations

11.

Pamuła, T.. (2016). CLASSIFICATION OF ROAD TRAFFIC CONDITIONS BASED ON TEXTURE FEATURES OF TRAFFIC IMAGES USING NEURAL NETWORKS. Scientific Journal of Silesian University of Technology Series Transport. 92. 101–109. 4 indexed citations

12.

Pamuła, T.. (2014). Model predykcji natężenia ruchu pojazdów z użyciem sztucznych sieci neuronowych. Logistyka.

13.

Bernaś, Marcin, Bartłomiej Płaczek, Piotr Porwik, & T. Pamuła. (2014). Segmentation of vehicle detector data for improved k‐nearest neighbours‐based traffic flow prediction. IET Intelligent Transport Systems. 9(3). 264–274. 41 indexed citations

14.

Pamuła, T.. (2012). Prognozowanie natężenia ruchu pojazdów na skrzyżowaniu za pomocą sieci neuronowej. Zeszyty Naukowe. Transport / Politechnika Śląska. 67–74. 2 indexed citations

15.

Pamuła, T.. (2012). Classification and Prediction of Traffic Flow Based on Real Data Using Neural Networks. Archives of Transport. 24(4). 13 indexed citations

16.

Pamuła, T.. (2011). Road traffic parameters prediction in urban traffic management systems using neural networks. SHILAP Revista de lepidopterología. 22 indexed citations

17.

Pamuła, T., et al.. (2010). MODEL SYSTEMU ZARZ ĄDZANIA RUCHEM POJAZDÓW W OBSZARZE MIEJSKIM Z WYKORZYSTANIEM SIECI NEURONOWYCH. Zeszyty Naukowe. Transport / Politechnika Śląska. 91–96. 1 indexed citations

18.

Król, Aleksander & T. Pamuła. (2009). Using a genetic algorithm for the design of an optimal transport network. SHILAP Revista de lepidopterología.

19.

Pamuła, T. & Aleksander Król. (2009). Statystyczny model monitorowania ruchu drogowego. Zeszyty Naukowe. Transport / Politechnika Śląska. 73–80. 2 indexed citations

20.

Pamuła, T., et al.. (2006). Metoda identyfikacji znaków szczególnych pojazdów samochodowych. Transport Problems. 241–248.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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