Marcello Trovati
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Environmental Engineering top 10%
- Management Science and Operations Research top 5%
- Signal Processing top 5%
- Co-authors
- Ella PereiraArdhendu BeheraPradeep HewageFrancesco PalmieriYonghuai LiuMorteza GhahremaniNik BessisXiaolong Xu
- Topics
- Complex Network Analysis Techniques (10 papers)Network Security and Intrusion Detection (5 papers)Advanced Text Analysis Techniques (5 papers)
- Journals
- IEEE Transactions on Industrial InformaticsIEEE Internet of Things JournalApplied Soft Computing
- Partner nations
- United KingdomChinaItaly
In The Last Decade
Marcello Trovati
43 papers receiving 863 citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Artificial Intelligence 247
- Electrical and Electronic Engineering 194
- Environmental Engineering 138
- Management Science and Operations Research 116
- Signal Processing 112
Countries citing papers authored by Marcello Trovati
This map shows the geographic impact of Marcello Trovati'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 Marcello Trovati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcello Trovati more than expected).
Fields of papers citing papers by Marcello Trovati
This network shows the impact of papers produced by Marcello Trovati. 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 Marcello Trovati. The network helps show where Marcello Trovati may publish in the future.
Co-authorship network of co-authors of Marcello Trovati
This figure shows the co-authorship network connecting the top 25 collaborators of Marcello Trovati. A scholar is included among the top collaborators of Marcello Trovati 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 Marcello Trovati. Marcello Trovati is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 6 | |
| 8 | 3 | |
| 9 | 18 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 147 | |
| 13 | Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather stationbreakdown → | 370 |
| 14 | 8 | |
| 15 | 6 | |
| 16 | 9 | |
| 17 | 43 | |
| 18 | 73 | |
| 19 | 6 | |
| 20 | 10 |
About Marcello Trovati
Marcello Trovati is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Software, having authored 49 papers that have together received 893 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Network Security and Intrusion Detection (5 papers) and Advanced Text Analysis Techniques (5 papers). The work is most often cited by research in Signal Processing (112 citations), Environmental Engineering (138 citations) and Management Science and Operations Research (116 citations). Marcello Trovati has collaborated with scholars based in United Kingdom, China and Italy. Frequent co-authors include Ella Pereira, Ardhendu Behera, Pradeep Hewage, Francesco Palmieri, Yonghuai Liu, Morteza Ghahremani, Nik Bessis, Xiaolong Xu, Mark Liptrott and Hao Yuan. Their work appears in journals such as IEEE Transactions on Industrial Informatics, IEEE Internet of Things Journal and Applied Soft Computing.
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.