Amelia Zafra

1.9k citations
45 papers · 1.2k indexed · h-index 19
Topics
Evolutionary Algorithms and Applications (18 papers)Metaheuristic Optimization Algorithms Research (15 papers)Image Retrieval and Classification Techniques (12 papers)

In The Last Decade

Amelia Zafra

41 papers receiving 1.1k citations

Peers

Amelia Zafra
Comparison fields: 5 of 102
  • Artificial Intelligence 668
  • Computer Science Applications 464
  • Information Systems 353
  • Computer Vision and Pattern Recognition 186
  • Education 111
Replace Juan A. Lara with:
Juan A. Lara Spain
María A. Martínez Spain
Juan F. Huete Spain
Abdulrahman Altalhi Saudi Arabia
Rajni Jindal India
Kevin A. Schneider Canada
Lucas Drumond Germany
Tak-Lam Wong Hong Kong
Nazlia Omar Malaysia
Francisco García‐Sánchez Spain
Amelia Zafra relative to Juan A. Lara Spain Juan A. Lara's profile →
Citations per field
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Juan A. Lara · 1×
Citations per year

Countries citing papers authored by Amelia Zafra

Since Specialization
Citations

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

Fields of papers citing papers by Amelia Zafra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amelia Zafra

This figure shows the co-authorship network connecting the top 25 collaborators of Amelia Zafra. A scholar is included among the top collaborators of Amelia Zafra 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 Amelia Zafra. Amelia Zafra 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 2
2 2
3 7
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5 37
6 60
7 9
8
A Hybrid Multi-Criteria Approach Using a Genetic Algorithm for Recommending Courses to University Students.
13
9
A classification module for genetic programming algorithms in JCLEC
16
10 13
11 84
12 30
13 10
14 45
15 24
16
Predicting Student Grades in Learning Management Systems with Multiple Instance Genetic Programming.
44
17 14
18 18
19 28
20 1

About Amelia Zafra

Amelia Zafra is a scholar working on Computer Science Applications, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 45 papers that have together received 1.2k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (18 papers), Metaheuristic Optimization Algorithms Research (15 papers) and Image Retrieval and Classification Techniques (12 papers). The work is most often cited by research in Computer Science Applications (464 citations), Artificial Intelligence (668 citations) and Information Systems (353 citations). Amelia Zafra has collaborated with scholars based in Spain, Netherlands and Saudi Arabia. Frequent co-authors include Sebastián Ventura, Cristóbal Romero, Alberto Cano, Pedro G. Espejo, José Raúl Romero, Paul De Bra, César Hervás‐Martínez, Eva Gibaja, José María Luna and Mykola Pechenizkiy. Their work appears in journals such as Expert Systems with Applications, Computers & Education and Information Sciences.

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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