Tiago A. E. Ferreira

1.4k citations
79 papers · 911 indexed · h-index 18
Topics
Stock Market Forecasting Methods (28 papers)Neural Networks and Applications (23 papers)Complex Systems and Time Series Analysis (18 papers)
Journals
SHILAP Revista de lepidopterologíaRenewable and Sustainable Energy ReviewsPLoS ONE
Partner nations
BrazilFranceCanada

In The Last Decade

Tiago A. E. Ferreira

71 papers receiving 860 citations

Peers

Tiago A. E. Ferreira
Comparison fields: 5 of 113
  • Management Science and Operations Research 287
  • Artificial Intelligence 263
  • Electrical and Electronic Engineering 202
  • Economics and Econometrics 143
  • Environmental Engineering 123
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Milan Stehlík Austria
Germán Aneiros Spain
Taeryon Choi South Korea
A.P. de Weijer Netherlands
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Tiago A. E. Ferreira relative to Mayer Alvo Canada Mayer Alvo's profile →
Citations per field
00.5×8.1×
Mayer Alvo · 1×
Citations per year

Countries citing papers authored by Tiago A. E. Ferreira

Since Specialization
Citations

This map shows the geographic impact of Tiago A. E. Ferreira'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 Tiago A. E. Ferreira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tiago A. E. Ferreira more than expected).

Fields of papers citing papers by Tiago A. E. Ferreira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tiago A. E. Ferreira. 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 Tiago A. E. Ferreira. The network helps show where Tiago A. E. Ferreira may publish in the future.

Co-authorship network of co-authors of Tiago A. E. Ferreira

This figure shows the co-authorship network connecting the top 25 collaborators of Tiago A. E. Ferreira. A scholar is included among the top collaborators of Tiago A. E. Ferreira 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 Tiago A. E. Ferreira. Tiago A. E. Ferreira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 21
3 0
4 5
5 17
6 2
7 41
8 33
9 1
10 2
11 14
12 16
13 35
14 8
15 0
16
A hybrid method for tuning neural network for financial time series forecasting
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17 3
18 18
19
Time series forecasting with Qubit Neural Networks
5
20 3

About Tiago A. E. Ferreira

Tiago A. E. Ferreira is a scholar working on Management Science and Operations Research, Acoustics and Ultrasonics and Artificial Intelligence, having authored 79 papers that have together received 911 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (28 papers), Neural Networks and Applications (23 papers) and Complex Systems and Time Series Analysis (18 papers). The work is most often cited by research in Management Science and Operations Research (287 citations), Statistics and Probability (82 citations) and Environmental Engineering (123 citations). Tiago A. E. Ferreira has collaborated with scholars based in Brazil, France and Canada. Frequent co-authors include Paulo S. G. de Mattos Neto, Ricardo de A. Araújo, Germano C. Vasconcelos, Paulo J. L. Adeodato, Paulo Renato Alves Firmino, Adenilton J. da Silva, Francisco Madeiro, George D. C. Cavalcanti, Christophe Chesneau and Tatijana Stošić. Their work appears in journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and PLoS ONE.

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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