Joaquín Derrac

7.4k total citations · 2 hit papers
21 papers, 5.7k citations indexed

About

Joaquín Derrac is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Joaquín Derrac has authored 21 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 7 papers in Computational Theory and Mathematics and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Joaquín Derrac's work include Machine Learning and Data Classification (11 papers), Evolutionary Algorithms and Applications (9 papers) and Metaheuristic Optimization Algorithms Research (8 papers). Joaquín Derrac is often cited by papers focused on Machine Learning and Data Classification (11 papers), Evolutionary Algorithms and Applications (9 papers) and Metaheuristic Optimization Algorithms Research (8 papers). Joaquín Derrac collaborates with scholars based in Spain, United Kingdom and Saudi Arabia. Joaquín Derrac's co-authors include Francisco Herrera, Salvador García, Daniel Molina, José-Ramón Cano, Isaac Triguero, Chris Cornelis, Ponnuthurai Nagaratnam Suganthan, Francisco Chiclana, Steven Schockaert and Julián Luengo and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Information Sciences.

In The Last Decade

Joaquín Derrac

21 papers receiving 5.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms

2011 4.3k citations Joaquín Derrac, Salvador García et al. Swarm and Evolutionary Computation profile →
Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study

2011 460 citations Salvador García, Joaquín Derrac et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Joaquín Derrac Spain	17	3.9k	1.8k	905	564	536	21	5.7k
Manuel Lozano Spain	38	4.3k 1.1×	2.3k 1.2×	536 0.6×	516 0.9×	700 1.3×	86	6.4k
Ferrante Neri United Kingdom	44	4.4k 1.1×	2.8k 1.5×	661 0.7×	851 1.5×	467 0.9×	174	6.9k
Hamid R. Tizhoosh Canada	34	4.8k 1.2×	1.9k 1.0×	1.7k 1.8×	948 1.7×	381 0.7×	185	7.7k
Qiuzhen Lin China	43	3.4k 0.9×	2.7k 1.5×	645 0.7×	464 0.8×	418 0.8×	264	5.9k
Sanyang Liu China	32	2.7k 0.7×	2.1k 1.1×	708 0.8×	544 1.0×	508 0.9×	389	6.2k
Yongquan Zhou China	41	3.4k 0.9×	1.3k 0.7×	1.0k 1.2×	821 1.5×	956 1.8×	302	6.2k
Zexuan Zhu China	40	2.9k 0.8×	1.8k 1.0×	638 0.7×	344 0.6×	336 0.6×	165	5.7k
Shahryar Rahnamayan Canada	33	4.8k 1.2×	2.8k 1.5×	704 0.8×	800 1.4×	503 0.9×	194	6.8k
Zhihua Cai China	49	4.1k 1.0×	1.8k 1.0×	1.3k 1.4×	753 1.3×	172 0.3×	224	7.2k
Kusum Deep India	35	3.1k 0.8×	1.6k 0.9×	645 0.7×	972 1.7×	618 1.2×	184	5.7k

Countries citing papers authored by Joaquín Derrac

Since Specialization

Citations

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

Fields of papers citing papers by Joaquín Derrac

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joaquín Derrac

This figure shows the co-authorship network connecting the top 25 collaborators of Joaquín Derrac. A scholar is included among the top collaborators of Joaquín Derrac 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 Joaquín Derrac. Joaquín Derrac 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

Derrac, Joaquín, Francisco Chiclana, Salvador García, & Francisco Herrera. (2015). An Interval Valued K-Nearest Neighbors Classifier. Advances in intelligent systems research. 89. 12 indexed citations

Derrac, Joaquín & Steven Schockaert. (2015). Inducing semantic relations from conceptual spaces: A data-driven approach to plausible reasoning. Artificial Intelligence. 228. 66–94. 33 indexed citations

Galar, Mikel, Joaquín Derrac, Daniel Peralta, et al.. (2015). A survey of fingerprint classification Part I: Taxonomies on feature extraction methods and learning models. Knowledge-Based Systems. 81. 76–97. 55 indexed citations

Verbiest, Nele, Joaquín Derrac, Chris Cornelis, Salvador García, & Francisco Herrera. (2015). Evolutionary wrapper approaches for training set selection as preprocessing mechanism for support vector machines: Experimental evaluation and support vector analysis. Applied Soft Computing. 38. 10–22. 43 indexed citations

Galar, Mikel, Joaquín Derrac, Daniel Peralta, et al.. (2015). A survey of fingerprint classification Part II: Experimental analysis and ensemble proposal. Knowledge-Based Systems. 81. 98–116. 37 indexed citations

Sáez, José A., Joaquín Derrac, Julián Luengo, & Francisco Herrera. (2014). Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers. Pattern Recognition. 47(12). 3941–3948. 29 indexed citations

García, Salvador, Joaquín Derrac, Sergio Ramírez‐Gallego, & Francisco Herrera. (2014). On the statistical analysis of the parameters’ trend in a machine learning algorithm. Progress in Artificial Intelligence. 3(1). 51–53. 2 indexed citations

Derrac, Joaquín, et al.. (2014). Analyzing convergence performance of evolutionary algorithms: A statistical approach. Information Sciences. 289. 41–58. 130 indexed citations

Derrac, Joaquín, et al.. (2013). Statistical analysis of convergence performance throughout the evolutionary search: A case study with SaDE-MMTS and Sa-EPSDE-MMTS. 151–156. 14 indexed citations

10.

Derrac, Joaquín, Salvador García, & Francisco Herrera. (2013). Fuzzy nearest neighbor algorithms: Taxonomy, experimental analysis and prospects. Information Sciences. 260. 98–119. 94 indexed citations

11.

Triguero, Isaac, Joaquín Derrac, Salvador García, & Francisco Herrera. (2012). Integrating a differential evolution feature weighting scheme into prototype generation. Neurocomputing. 97. 332–343. 20 indexed citations

12.

García, Salvador, Joaquín Derrac, José-Ramón Cano, & Francisco Herrera. (2011). Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(3). 417–435. 460 indexed citations breakdown →

13.

Derrac, Joaquín, Salvador García, Daniel Molina, & Francisco Herrera. (2011). A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm and Evolutionary Computation. 1(1). 3–18. 4303 indexed citations breakdown →

14.

Triguero, Isaac, Joaquín Derrac, Salvador García, & Francisco Herrera. (2011). A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews). 42(1). 86–100. 169 indexed citations

15.

Derrac, Joaquín, Chris Cornelis, Salvador García, & Francisco Herrera. (2011). Enhancing evolutionary instance selection algorithms by means of fuzzy rough set based feature selection. Information Sciences. 186(1). 73–92. 97 indexed citations

16.

Derrac, Joaquín, Salvador García, & Francisco Herrera. (2010). Stratified prototype selection based on a steady-state memetic algorithm: a study of scalability. Memetic Computing. 2(3). 183–199. 24 indexed citations

17.

Derrac, Joaquín, Salvador García, & Francisco Herrera. (2010). A Survey on Evolutionary Instance Selection and Generation. International Journal of Applied Metaheuristic Computing. 1(1). 60–92. 48 indexed citations

18.

García, Salvador, Joaquín Derrac, Julián Luengo, C. J. Carmona, & Francisco Herrera. (2010). Evolutionary selection of hyperrectangles in nested generalized exemplar learning. Applied Soft Computing. 11(3). 3032–3045. 16 indexed citations

19.

Derrac, Joaquín, Salvador García, & Francisco Herrera. (2009). IFS-CoCo: Instance and feature selection based on cooperative coevolution with nearest neighbor rule. Pattern Recognition. 43(6). 2082–2105. 67 indexed citations

20.

García, Salvador, Joaquín Derrac, Julián Luengo, & Francisco Herrera. (2009). A First Approach to Nearest Hyperrectangle Selection by Evolutionary Algorithms. 7. 517–522. 8 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