Khalid M. Salama

1.4k total citations
29 papers, 330 citations indexed

About

Khalid M. Salama is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Khalid M. Salama has authored 29 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 11 papers in Information Systems and 5 papers in Computational Theory and Mathematics. Recurrent topics in Khalid M. Salama's work include Metaheuristic Optimization Algorithms Research (17 papers), Machine Learning and Data Classification (13 papers) and Data Mining Algorithms and Applications (9 papers). Khalid M. Salama is often cited by papers focused on Metaheuristic Optimization Algorithms Research (17 papers), Machine Learning and Data Classification (13 papers) and Data Mining Algorithms and Applications (9 papers). Khalid M. Salama collaborates with scholars based in United Kingdom, Canada and Egypt. Khalid M. Salama's co-authors include Ashraf M. Abdelbar, Alex A. Freitas, Fernando E. B. Otero, Barbara McGillivray, João Pedro de Magalhães, Fábio Fabris, Daniel H. Palmer, Ayah Helal, Jesús Guillermo Falcón-Cardona and Carlos A. Coello Coello and has published in prestigious journals such as Bioinformatics, IEEE Access and Applied Soft Computing.

In The Last Decade

Khalid M. Salama

28 papers receiving 319 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Khalid M. Salama United Kingdom 12 254 88 43 28 26 29 330
Janusz Wnek United States 9 179 0.7× 75 0.9× 69 1.6× 10 0.4× 9 0.3× 25 255
Naveen Saini India 10 270 1.1× 45 0.5× 37 0.9× 7 0.3× 8 0.3× 30 325
Karl Pfleger United States 5 117 0.5× 58 0.7× 27 0.6× 21 0.8× 4 0.2× 7 166
Michal W. Przewozniczek Poland 10 168 0.7× 34 0.4× 119 2.8× 44 1.6× 23 0.9× 47 289
Devottam Gaurav India 6 111 0.4× 54 0.6× 6 0.1× 61 2.2× 6 0.2× 10 240
Mark‐Oliver Reiser Germany 9 173 0.7× 145 1.6× 41 1.0× 43 1.5× 12 0.5× 28 257
Nicholas Holden United Kingdom 5 178 0.7× 48 0.5× 58 1.3× 9 0.3× 5 0.2× 5 229
Daniel Weise United States 9 257 1.0× 121 1.4× 121 2.8× 58 2.1× 4 0.2× 32 390
Hiroshi Tsukimoto Japan 5 157 0.6× 35 0.4× 46 1.1× 17 0.6× 6 0.2× 12 213
Hirotoshi Yasuoka Japan 6 115 0.5× 31 0.4× 21 0.5× 22 0.8× 6 0.2× 7 182

Countries citing papers authored by Khalid M. Salama

Since Specialization
Citations

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

Fields of papers citing papers by Khalid M. Salama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Khalid M. Salama. 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 Khalid M. Salama. The network helps show where Khalid M. Salama may publish in the future.

Co-authorship network of co-authors of Khalid M. Salama

This figure shows the co-authorship network connecting the top 25 collaborators of Khalid M. Salama. A scholar is included among the top collaborators of Khalid M. Salama 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 Khalid M. Salama. Khalid M. Salama 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
1.
McGillivray, Barbara, et al.. (2022). Investigating patterns of change, stability, and interaction among scientific disciplines using embeddings. Humanities and Social Sciences Communications. 9(1). 18 indexed citations
2.
Abdelbar, Ashraf M. & Khalid M. Salama. (2019). Parameter Self-Adaptation in an Ant Colony Algorithm for Continuous Optimization. IEEE Access. 7. 18464–18479. 15 indexed citations
3.
Abdelbar, Ashraf M., Khalid M. Salama, Jesús Guillermo Falcón-Cardona, & Carlos A. Coello Coello. (2018). An Adaptive Recombination-Based Extension of the iMOACO<inf>R</inf> Algorithm. 735–742. 1 indexed citations
4.
Abdelbar, Ashraf M., et al.. (2018). Matrix Factorization Based Collaborative Filtering With Resilient Stochastic Gradient Descent. 3. 1–7. 1 indexed citations
5.
Salama, Khalid M. & Ashraf M. Abdelbar. (2017). Learning cluster-based classification systems with ant colony optimization algorithms. Swarm Intelligence. 11(3-4). 211–242. 7 indexed citations
6.
Abdelbar, Ashraf M. & Khalid M. Salama. (2017). A sugeno-based search width decay schedule in the ACO<inf>R</inf> algorithm. 1–8. 2 indexed citations
7.
Abdelbar, Ashraf M. & Khalid M. Salama. (2017). Solution recombination in an indicator-based many-objective ant colony optimizer for continuous search spaces. 1–8. 3 indexed citations
8.
Salama, Khalid M., et al.. (2016). Data reduction for classification with ant colony algorithms. Intelligent Data Analysis. 20(5). 1021–1059. 11 indexed citations
9.
Abdelbar, Ashraf M. & Khalid M. Salama. (2016). An extension of the ACO<inf>R</inf> algorithm with time-decaying search width, with application to neural network training. 2360–2366. 4 indexed citations
10.
Salama, Khalid M. & Ashraf M. Abdelbar. (2015). Learning neural network structures with ant colony algorithms. Swarm Intelligence. 9(4). 229–265. 39 indexed citations
11.
Abdelbar, Ashraf M. & Khalid M. Salama. (2015). A Gradient-Guided ACO Algorithm for Neural Network Learning. 1133–1140. 10 indexed citations
12.
Salama, Khalid M., et al.. (2015). ADR-Miner: An ant-based data reduction algorithm for classification. 515–521. 8 indexed citations
13.
Salama, Khalid M. & Alex A. Freitas. (2014). Classification with cluster-based Bayesian multi-nets using Ant Colony Optimisation. Swarm and Evolutionary Computation. 18. 54–70. 12 indexed citations
14.
Salama, Khalid M. & Alex A. Freitas. (2014). ABC-Miner+: constructing Markov blanket classifiers with ant colony algorithms. Memetic Computing. 6(3). 183–206. 8 indexed citations
15.
Salama, Khalid M. & Fernando E. B. Otero. (2014). Learning Multi-tree Classification Models with Ant Colony Optimization. Kent Academic Repository (University of Kent). 38–48. 11 indexed citations
16.
Salama, Khalid M. & Fernando E. B. Otero. (2013). Using a unified measure function for heuristics, discretization, and rule quality evaluation in Ant-Miner. Kent Academic Repository (University of Kent). 9. 900–907. 4 indexed citations
17.
Salama, Khalid M. & Alex A. Freitas. (2013). Investigating the impact of various classification quality measures in the predictive accuracy of ABC-Miner. Kent Academic Repository (University of Kent). 9. 2321–2328. 1 indexed citations
18.
Salama, Khalid M., Ashraf M. Abdelbar, Fernando E. B. Otero, & Alex A. Freitas. (2012). Utilizing multiple pheromones in an ant-based algorithm for continuous-attribute classification rule discovery. Applied Soft Computing. 13(1). 667–675. 30 indexed citations
19.
Salama, Khalid M., Ashraf M. Abdelbar, & Alex A. Freitas. (2011). Multiple pheromone types and other extensions to the Ant-Miner classification rule discovery algorithm. Swarm Intelligence. 5(3-4). 149–182. 38 indexed citations
20.
Salama, Khalid M. & Ashraf M. Abdelbar. (2011). Exploring different rule quality evaluation functions in ACO-based classification algorithms. 5217. 1–8. 9 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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