A.E. Ruano

4.3k total citations
156 papers, 3.1k citations indexed

About

A.E. Ruano is a scholar working on Artificial Intelligence, Control and Systems Engineering and Building and Construction. According to data from OpenAlex, A.E. Ruano has authored 156 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Artificial Intelligence, 43 papers in Control and Systems Engineering and 36 papers in Building and Construction. Recurrent topics in A.E. Ruano's work include Building Energy and Comfort Optimization (36 papers), Neural Networks and Applications (36 papers) and Advanced Control Systems Optimization (21 papers). A.E. Ruano is often cited by papers focused on Building Energy and Comfort Optimization (36 papers), Neural Networks and Applications (36 papers) and Advanced Control Systems Optimization (21 papers). A.E. Ruano collaborates with scholars based in Portugal, Hungary and Spain. A.E. Ruano's co-authors include Pedro Ferreira, Eusébio Conceição, M.G. Ruano, Álvaro Hernández, J.J. Garcı́a, Jesús Ureña, Maria Manuela Lúcio, László T. Kóczy, Urbano Nunes and P.J. Fleming and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Energy Conversion and Management.

In The Last Decade

A.E. Ruano

148 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A.E. Ruano Portugal	28	1.1k	1.0k	741	645	415	156	3.1k
Pedro Ferreira Portugal	24	472 0.4×	623 0.6×	396 0.5×	420 0.7×	237 0.6×	124	2.1k
Elias B. Kosmatopoulos Greece	38	1.3k 1.2×	1.9k 1.9×	686 0.9×	2.9k 4.5×	339 0.8×	197	5.5k
Xinqiao Jin China	32	724 0.7×	1.8k 1.8×	372 0.5×	957 1.5×	380 0.9×	98	3.1k
Prabir Barooah United States	31	1.7k 1.6×	1.6k 1.5×	195 0.3×	1.3k 2.1×	459 1.1×	120	3.9k
Alfonso Capozzoli Italy	35	1.4k 1.3×	2.6k 2.5×	395 0.5×	555 0.9×	813 2.0×	111	4.1k
Guannan Li China	31	707 0.7×	1.2k 1.1×	307 0.4×	664 1.0×	294 0.7×	81	2.3k
Sutharshan Rajasegarar Australia	30	1.0k 1.0×	625 0.6×	2.3k 3.1×	665 1.0×	172 0.4×	110	4.6k
Álvaro Gutiérrez Spain	20	826 0.8×	480 0.5×	218 0.3×	361 0.6×	190 0.5×	92	1.8k
Alberto Cerpa United States	27	1.9k 1.8×	1.1k 1.0×	237 0.3×	139 0.2×	367 0.9×	71	4.3k

Countries citing papers authored by A.E. Ruano

Since Specialization

Citations

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

Fields of papers citing papers by A.E. Ruano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A.E. Ruano

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Fisch, Gilberto, et al.. (2025). Anomaly detection in all-sky images: An approach using robust ensemble modeling of cloud cover fraction and prediction bounds. Engineering Applications of Artificial Intelligence. 143. 110003–110003.

Ruano, A.E. & M.G. Ruano. (2024). From home energy management systems to energy communities: methods and data. Scientific Data. 11(1). 346–346. 5 indexed citations

Ruano, A.E. & M.G. Ruano. (2023). Designing Robust Forecasting Ensembles of Data-Driven Models with a Multi-Objective Formulation: An Application to Home Energy Management Systems. Inventions. 8(4). 96–96. 3 indexed citations

Gomes, I.L.R., M.G. Ruano, & A.E. Ruano. (2023). From home energy management systems to communities energy managers: The use of an intelligent aggregator in a community in Algarve, Portugal. Energy and Buildings. 298. 113588–113588. 8 indexed citations

Fadili, Hakim El, et al.. (2022). A comprehensive review of solar irradiation estimation and forecasting using artificial neural networks: data, models and trends. Environmental Science and Pollution Research. 30(3). 5407–5439. 23 indexed citations

Hernández, Álvaro, A.E. Ruano, Jesús Ureña, M.G. Ruano, & J.J. Garcı́a. (2019). Applications of NILM Techniques to Energy Management and Assisted Living. IFAC-PapersOnLine. 52(11). 164–171. 20 indexed citations

Pau, Giovanni, Mario Collotta, A.E. Ruano, & Jiahu Qin. (2017). Smart Home Energy Management. Energies. 10(3). 382–382. 43 indexed citations

Ruano, A.E., et al.. (2015). An Intelligent Weather Station. Sensors. 15(12). 31005–31022. 42 indexed citations

Ferreira, Pedro, et al.. (2012). Neural networks based predictive control for thermal comfort and energy savings in public buildings. Energy and Buildings. 55. 238–251. 362 indexed citations

10.

Gál, László, János Botzheim, László T. Kóczy, & A.E. Ruano. (2009). Applying Bacterial Memetic Algorithm for Training Feedforward and Fuzzy Flip-Flop based Neural Networks. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 1833–1838. 5 indexed citations

11.

Teixeira, César, et al.. (2009). On the possibility of non-invasive multilayer temperature estimation using soft-computing methods. Ultrasonics. 50(1). 32–43. 15 indexed citations

12.

Teixeira, César, M.G. Ruano, A.E. Ruano, & Wagner Coelho de Albuquerque Pereira. (2008). Neuro-genetic non-invasive temperature estimation: Intensity and spatial prediction. Artificial Intelligence in Medicine. 43(2). 127–139. 3 indexed citations

13.

Ruano, A.E., et al.. (2006). Application of Levenberg-Marquardt method to the training of spiking neural networks. 3. 1354–1358. 19 indexed citations

14.

Teixeira, César, et al.. (2006). Non-invasive temperature prediction of in vitro therapeutic ultrasound signals using neural networks. Medical & Biological Engineering & Computing. 44(1-2). 111–116. 11 indexed citations

15.

Teixeira, César, et al.. (2004). Temperature models of a homogeneous medium under therapeutic ultrasound. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 2 indexed citations

16.

Botzheim, János, et al.. (2003). Genetic programming and bacterial algorithm for neural networks and fuzzy systems design. Sapientia (Algarve University). 1 indexed citations

17.

Leva, Alberto, et al.. (2002). Hands-on PID autotuning: a guide to better utilisation. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 25 indexed citations

18.

Ruano, A.E., et al.. (2002). Some questions of condition monitoring of turbopropengine transmission. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 1 indexed citations

19.

Nunes, Urbano, et al.. (2002). Obstacle Avoidance in Local Navigation. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 9 indexed citations

20.

Ruano, A.E., et al.. (1996). Comparison of alternative approaches to neural network PID autotuning. Sapientia (Algarve University). 2 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.

Explore authors with similar magnitude of impact