Fana Tangara

641 total citations · 1 hit paper
13 papers, 420 citations indexed

About

Fana Tangara is a scholar working on Artificial Intelligence, Management Information Systems and Information Systems. According to data from OpenAlex, Fana Tangara has authored 13 papers receiving a total of 420 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Management Information Systems and 3 papers in Information Systems. Recurrent topics in Fana Tangara's work include Business Process Modeling and Analysis (3 papers), Advanced machining processes and optimization (3 papers) and Hydrological Forecasting Using AI (2 papers). Fana Tangara is often cited by papers focused on Business Process Modeling and Analysis (3 papers), Advanced machining processes and optimization (3 papers) and Hydrological Forecasting Using AI (2 papers). Fana Tangara collaborates with scholars based in Mali, France and United States. Fana Tangara's co-authors include Bernard Kamsu-Foguem and Lionel Arnaud and has published in prestigious journals such as Expert Systems with Applications, Sustainable Cities and Society and The International Journal of Advanced Manufacturing Technology.

In The Last Decade

Fana Tangara

11 papers receiving 397 citations

Hit Papers

Deep convolution neural network for image recognition 2018 2026 2020 2023 2018 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fana Tangara Mali 9 83 76 55 46 43 13 420
Jibitesh Mishra India 12 61 0.7× 143 1.9× 44 0.8× 44 1.0× 31 0.7× 67 567
Vyacheslav Lyashenko Ukraine 12 69 0.8× 78 1.0× 57 1.0× 14 0.3× 35 0.8× 125 532
Rafael Gomes Mantovani Brazil 12 239 2.9× 76 1.0× 29 0.5× 30 0.7× 24 0.6× 34 594
Meili Sun China 7 138 1.7× 77 1.0× 34 0.6× 162 3.5× 38 0.9× 10 598
Ignacio Heredia Spain 4 175 2.1× 69 0.9× 19 0.3× 26 0.6× 23 0.5× 15 545
Kuang Yu Huang Taiwan 12 105 1.3× 175 2.3× 49 0.9× 104 2.3× 52 1.2× 28 720
Nikita Andriyanov Russia 13 74 0.9× 148 1.9× 22 0.4× 77 1.7× 29 0.7× 78 494
S. Margret Anouncia India 10 63 0.8× 68 0.9× 33 0.6× 19 0.4× 16 0.4× 56 312
Roobaea Alroobaea Saudi Arabia 12 133 1.6× 146 1.9× 17 0.3× 27 0.6× 31 0.7× 39 537

Countries citing papers authored by Fana Tangara

Since Specialization
Citations

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

Fields of papers citing papers by Fana Tangara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fana Tangara. 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 Fana Tangara. The network helps show where Fana Tangara may publish in the future.

Co-authorship network of co-authors of Fana Tangara

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

All Works

13 of 13 papers shown
1.
Arnaud, Lionel, et al.. (2023). Deep learning for the detection of machining vibration chatter. Advances in Engineering Software. 180. 103445–103445. 25 indexed citations
2.
Arnaud, Lionel, et al.. (2022). Review of AI-based methods for chatter detection in machining based on bibliometric analysis. The International Journal of Advanced Manufacturing Technology. 122(5-6). 2161–2186. 19 indexed citations
3.
Kamsu-Foguem, Bernard, et al.. (2022). Learning with deep Gaussian processes and homothety in weather simulation. Neural Computing and Applications. 34(20). 17441–17453. 2 indexed citations
4.
Tangara, Fana, et al.. (2022). Multimodal deep learning for predicting the choice of cut parameters in the milling process. Intelligent Systems with Applications. 16. 200112–200112. 10 indexed citations
5.
Kamsu-Foguem, Bernard, et al.. (2021). Explainability with Association Rule Learning for Weather Forecast. SN Computer Science. 2(2). 4 indexed citations
6.
Kamsu-Foguem, Bernard, et al.. (2020). Rule-based machine learning for knowledge discovering in weather data. Future Generation Computer Systems. 108. 861–878. 18 indexed citations
7.
Kamsu-Foguem, Bernard, et al.. (2018). Software services for supporting remote crisis management. Sustainable Cities and Society. 39. 814–827. 8 indexed citations
8.
Kamsu-Foguem, Bernard, et al.. (2018). Service-Oriented Computing for intelligent train maintenance. Enterprise Information Systems. 13(1). 63–86. 9 indexed citations
9.
Kamsu-Foguem, Bernard, et al.. (2018). Deep convolution neural network for image recognition. Ecological Informatics. 48. 257–268. 273 indexed citations breakdown →
10.
Kamsu-Foguem, Bernard, et al.. (2016). Data mining techniques on satellite images for discovery of risk areas. Expert Systems with Applications. 72. 443–456. 34 indexed citations
11.
Kamsu-Foguem, Bernard, et al.. (2015). Integrating MDA and SOA for improving telemedicine services. Telematics and Informatics. 33(3). 733–741. 18 indexed citations
12.
Tangara, Fana. (2010). Ap-Adic Quantum Weyl Algebra. Communications in Algebra. 38(6). 2300–2310.
13.
Tangara, Fana, et al.. (2009). The p-adic quantum plane algebras and quantum Weyl algebra. P-Adic Numbers Ultrametric Analysis and Applications. 1(2). 128–135.

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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