Pierpaolo D’Urso
- Artificial Intelligence top 1%
- Signal Processing top 0.5%
- Economics and Econometrics top 1%
- Statistics and Probability top 0.2%
- Management Science and Operations Research top 0.5%
- Co-authors
- Riccardo MassariElizabeth Ann MaharajLivia De GiovanniPaolo GiordaniRenato CoppiMarta DisegnaJacek M. ŁęskiJosé A. Vilar
- Topics
- Time Series Analysis and Forecasting (47 papers)Complex Systems and Time Series Analysis (41 papers)Fuzzy Systems and Optimization (34 papers)
- Journals
- SHILAP Revista de lepidopterologíaTourism ManagementExpert Systems with Applications
In The Last Decade
Pierpaolo D’Urso
128 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 133
- Artificial Intelligence 1.4k
- Signal Processing 1.1k
- Economics and Econometrics 1.1k
- Statistics and Probability 993
- Management Science and Operations Research 941
Countries citing papers authored by Pierpaolo D’Urso
This map shows the geographic impact of Pierpaolo D’Urso'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 Pierpaolo D’Urso with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierpaolo D’Urso more than expected).
Fields of papers citing papers by Pierpaolo D’Urso
This network shows the impact of papers produced by Pierpaolo D’Urso. 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 Pierpaolo D’Urso. The network helps show where Pierpaolo D’Urso may publish in the future.
Co-authorship network of co-authors of Pierpaolo D’Urso
This figure shows the co-authorship network connecting the top 25 collaborators of Pierpaolo D’Urso. A scholar is included among the top collaborators of Pierpaolo D’Urso 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 Pierpaolo D’Urso. Pierpaolo D’Urso is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 4 | |
| 10 | 18 | |
| 11 | 17 | |
| 12 | 3 | |
| 13 | 12 | |
| 14 | 17 | |
| 15 | 47 | |
| 16 | 2 | |
| 17 | Informational Paradigm, Management of Uncertainty and Theoretical Formalisms in the Clustering Framework: a Review | 1 |
| 18 | 38 | |
| 19 | Statistics with Fuzzy Random Variables | 15 |
| 20 | FITTING OF FUZZY LINEAR REGRESSION MODELS WITH MULTIVARIATE RESPONSE | 5 |
About Pierpaolo D’Urso
Pierpaolo D’Urso is a scholar working on Signal Processing, Statistics and Probability and Management Science and Operations Research, having authored 134 papers that have together received 3.4k indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (47 papers), Complex Systems and Time Series Analysis (41 papers) and Fuzzy Systems and Optimization (34 papers). The work is most often cited by research in Statistics and Probability (993 citations), Signal Processing (1.1k citations) and Management Science and Operations Research (941 citations). Pierpaolo D’Urso has collaborated with scholars based in Italy, Spain and Australia. Frequent co-authors include Riccardo Massari, Elizabeth Ann Maharaj, Livia De Giovanni, Paolo Giordani, Renato Coppi, Marta Disegna, Jacek M. Łęski, José A. Vilar, Jorge Caiado and Linda Osti. Their work appears in journals such as SHILAP Revista de lepidopterología, Tourism Management and Expert Systems with Applications.
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.