Gehad Ismail Sayed

2.4k citations
38 papers · 1.6k indexed · 2 hit papers · h-index 15

Gehad Ismail Sayed

37 papers receiving 1.6k citations

Hit Papers

A novel chaotic salp swarm algorithm for global optimizat...3452017202620202023100200300

Peers

Gehad Ismail Sayed
Comparison fields: 5 of 122
  • Artificial Intelligence 1.1k
  • Computational Theory and Mathematics 361
  • Computer Vision and Pattern Recognition 290
  • Industrial and Manufacturing Engineering 76
  • Health Information Management 34
Replace Qasem Al-Tashi with:
Qasem Al-Tashi Malaysia
Rehab Ali Ibrahim Egypt
Dong Zhao China
Mohammad Alshinwan Jordan
Yueting Xu China
Hoda Zamani Iran
Mohammed Alswaitti Malaysia
Shokooh Taghian Iran
Hang Su China
Gehad Ismail Sayed relative to Qasem Al-Tashi Malaysia Qasem Al-Tashi's profile →
Citations per field
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Qasem Al-Tashi · 1×
Citations per year

Countries citing papers authored by Gehad Ismail Sayed

Since Specialization
Citations

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

Fields of papers citing papers by Gehad Ismail Sayed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gehad Ismail Sayed. 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 Gehad Ismail Sayed. The network helps show where Gehad Ismail Sayed may publish in the future.

Co-authorship network

The 20 scholars most cited alongside Gehad Ismail Sayed, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gehad Ismail Sayed Line = papers co-authored together Gehad Ismail Sayed links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20250
3 20241
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5 20241
6 20243
7 20247
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9 20249
10 202414
11 20232
12 2021137
13 202130
14 20214
15 20196
16 201871
17 201860
18
A novel chaotic salp swarm algorithm for global optimization and feature selectionbreakdown →
2018345
19 201751
20 201546

About Gehad Ismail Sayed

Gehad Ismail Sayed is a scholar working on Artificial Intelligence, Neurology and Computer Vision and Pattern Recognition, having authored 38 papers that have together received 1.6k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (13 papers), Evolutionary Algorithms and Applications (7 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Brain Tumor Detection and Classification (4 papers), AI in cancer detection (4 papers), Artificial Immune Systems Applications (4 papers), Medical Image Segmentation Techniques (3 papers) and Energy Load and Power Forecasting (3 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Computational Theory and Mathematics (361 citations) and Computer Vision and Pattern Recognition (290 citations). Gehad Ismail Sayed has collaborated with scholars based in Egypt, Kuwait and Czechia. Frequent co-authors include Aboul Ella Hassanien, Mohamed H. Haggag, Ghada Khoriba, Ahmad Taher Azar, Alaa Tharwat, Mona Soliman, Ashraf Darwish, Ashraf Darwish, Václav Snåšel and Mona A. S. Ali. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Environmental Science and Pollution Research.

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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