Andrés L. Suárez‐Cetrulo

464 total citations
12 papers, 266 citations indexed

About

Andrés L. Suárez‐Cetrulo is a scholar working on Artificial Intelligence, Management Science and Operations Research and Signal Processing. According to data from OpenAlex, Andrés L. Suárez‐Cetrulo has authored 12 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Management Science and Operations Research and 3 papers in Signal Processing. Recurrent topics in Andrés L. Suárez‐Cetrulo's work include Data Stream Mining Techniques (5 papers), Stock Market Forecasting Methods (4 papers) and Time Series Analysis and Forecasting (3 papers). Andrés L. Suárez‐Cetrulo is often cited by papers focused on Data Stream Mining Techniques (5 papers), Stock Market Forecasting Methods (4 papers) and Time Series Analysis and Forecasting (3 papers). Andrés L. Suárez‐Cetrulo collaborates with scholars based in Ireland, Spain and Switzerland. Andrés L. Suárez‐Cetrulo's co-authors include Alejandro Cervantes, David Quintana, S. Alonso Monsalve, Ricardo Simón Carbajo, Rajnish Rakholia, Ankit Kumar, Luis Miralles‐Pechuán and Anna Queralt and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Renewable Energy.

In The Last Decade

Andrés L. Suárez‐Cetrulo

10 papers receiving 259 citations

Peers

Andrés L. Suárez‐Cetrulo
Rui Ren China
Liangxi Qin China
Renzhong Wang United States
Steven H. Kim South Korea
Xiongwen Pang China
Waldyn G. Martinez United States
S. Al Wadi Jordan
Riswan Efendi Indonesia
Akito Sakurai Japan
Jui-Yu Wu Taiwan
Rui Ren China
Andrés L. Suárez‐Cetrulo
Citations per year, relative to Andrés L. Suárez‐Cetrulo Andrés L. Suárez‐Cetrulo (= 1×) peers Rui Ren

Countries citing papers authored by Andrés L. Suárez‐Cetrulo

Since Specialization
Citations

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

Fields of papers citing papers by Andrés L. Suárez‐Cetrulo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrés L. Suárez‐Cetrulo. 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 Andrés L. Suárez‐Cetrulo. The network helps show where Andrés L. Suárez‐Cetrulo may publish in the future.

Co-authorship network of co-authors of Andrés L. Suárez‐Cetrulo

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

All Works

12 of 12 papers shown
1.
Suárez‐Cetrulo, Andrés L., et al.. (2025). Offloading artificial intelligence workloads across the computing continuum by means of active storage systems. Future Generation Computer Systems. 178. 108271–108271.
2.
Rakholia, Rajnish, et al.. (2025). AI-Driven Meat Food Drying Time Prediction for Resource Optimization and Production Planning in Smart Manufacturing. IEEE Access. 13. 22420–22428. 2 indexed citations
3.
Rakholia, Rajnish, et al.. (2025). Integrating AI and IoT for Predictive Maintenance in Industry 4.0 Manufacturing Environments: A Practical Approach. Information. 16(9). 737–737. 1 indexed citations
4.
Suárez‐Cetrulo, Andrés L., et al.. (2025). Intelligent Edge Computing and Machine Learning: A Survey of Optimization and Applications. Future Internet. 17(9). 417–417.
5.
Rakholia, Rajnish, et al.. (2024). Advancing Manufacturing Through Artificial Intelligence: Current Landscape, Perspectives, Best Practices, Challenges, and Future Direction. IEEE Access. 12. 131621–131637. 17 indexed citations
6.
Miralles‐Pechuán, Luis, Ankit Kumar, & Andrés L. Suárez‐Cetrulo. (2023). Forecasting COVID‐19 cases using dynamic time warping and incremental machine learning methods. Expert Systems. 40(6). 5 indexed citations
7.
Suárez‐Cetrulo, Andrés L., David Quintana, & Alejandro Cervantes. (2023). Machine Learning for Financial Prediction Under Regime Change Using Technical Analysis: A Systematic Review.. International Journal of Interactive Multimedia and Artificial Intelligence. 9(1). 137–148. 2 indexed citations
8.
Suárez‐Cetrulo, Andrés L., David Quintana, & Alejandro Cervantes. (2022). A survey on machine learning for recurring concept drifting data streams. Expert Systems with Applications. 213. 118934–118934. 60 indexed citations
9.
Suárez‐Cetrulo, Andrés L., et al.. (2022). Wind power forecasting using ensemble learning for day-ahead energy trading. Renewable Energy. 191. 685–698. 23 indexed citations
10.
Monsalve, S. Alonso, Andrés L. Suárez‐Cetrulo, Alejandro Cervantes, & David Quintana. (2020). Convolution on neural networks for high-frequency trend prediction of cryptocurrency exchange rates using technical indicators. Expert Systems with Applications. 149. 113250–113250. 136 indexed citations
11.
Suárez‐Cetrulo, Andrés L., Alejandro Cervantes, & David Quintana. (2019). Incremental Market Behavior Classification in Presence of Recurring Concepts. Entropy. 21(1). 25–25. 16 indexed citations
12.
Suárez‐Cetrulo, Andrés L. & Alejandro Cervantes. (2017). An online classification algorithm for large scale data streams: iGNGSVM. Neurocomputing. 262. 67–76. 4 indexed citations

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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