Ender Sevinç

1.3k total citations · 1 hit paper
18 papers, 946 citations indexed

About

Ender Sevinç is a scholar working on Artificial Intelligence, Computer Networks and Communications and Industrial and Manufacturing Engineering. According to data from OpenAlex, Ender Sevinç has authored 18 papers receiving a total of 946 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 5 papers in Computer Networks and Communications and 4 papers in Industrial and Manufacturing Engineering. Recurrent topics in Ender Sevinç's work include Metaheuristic Optimization Algorithms Research (7 papers), Machine Learning and ELM (7 papers) and Vehicle Routing Optimization Methods (4 papers). Ender Sevinç is often cited by papers focused on Metaheuristic Optimization Algorithms Research (7 papers), Machine Learning and ELM (7 papers) and Vehicle Routing Optimization Methods (4 papers). Ender Sevinç collaborates with scholars based in Türkiye and Spain. Ender Sevinç's co-authors include Tansel Dökeroğlu, Ahmet Coşar, Tayfun Küçükyılmaz, Murat Karakaya, Ayça Deniz, H. Yurtseven, Hakan Ezgi Kızılöz and Asuman Doğaç and has published in prestigious journals such as IEEE Access, Applied Soft Computing and Computers & Industrial Engineering.

In The Last Decade

Ender Sevinç

18 papers receiving 909 citations

Hit Papers

A survey on new generation metaheuristic algorithms 2019 2026 2021 2023 2019 200 400 600
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.

  1. A survey on new generation metaheuristic algorithms
    2019 649 citations Tansel Dökeroğlu, Ender Sevinç et al. Computers & Industrial Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ender Sevinç Türkiye 8 488 203 136 125 120 18 946
Tayfun Küçükyılmaz Türkiye 7 423 0.9× 166 0.8× 127 0.9× 96 0.8× 87 0.7× 13 829
Qidi Wu China 16 540 1.1× 229 1.1× 90 0.7× 196 1.6× 109 0.9× 87 1.0k
Itziar Landa-Torres Spain 14 323 0.7× 136 0.7× 118 0.9× 134 1.1× 99 0.8× 28 829
Halife Kodaz Türkiye 15 714 1.5× 227 1.1× 286 2.1× 93 0.7× 204 1.7× 41 1.2k
Ilhem Boussaïd Algeria 4 680 1.4× 398 2.0× 189 1.4× 136 1.1× 107 0.9× 4 1.3k
Miren Nekane Bilbao Spain 12 365 0.7× 105 0.5× 94 0.7× 105 0.8× 80 0.7× 35 774
Zahra Beheshti Iran 19 828 1.7× 347 1.7× 140 1.0× 154 1.2× 148 1.2× 32 1.3k
Junqi Zhang China 14 319 0.7× 126 0.6× 109 0.8× 185 1.5× 166 1.4× 64 771
Lam Thu Bui Vietnam 17 556 1.1× 418 2.1× 93 0.7× 119 1.0× 116 1.0× 69 1.1k

Countries citing papers authored by Ender Sevinç

Since Specialization
Citations

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

Fields of papers citing papers by Ender Sevinç

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ender Sevinç

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

All Works

18 of 18 papers shown
1.
Sevinç, Ender. (2022). An empowered AdaBoost algorithm implementation: A COVID-19 dataset study. Computers & Industrial Engineering. 165. 107912–107912. 69 indexed citations
2.
Deniz, Ayça, Hakan Ezgi Kızılöz, Ender Sevinç, & Tansel Dökeroğlu. (2022). Predicting the severity of COVID‐19 patients using a multi‐threaded evolutionary feature selection algorithm. Expert Systems. 39(5). 7 indexed citations
3.
Dökeroğlu, Tansel & Ender Sevinç. (2022). An island parallel Harris hawks optimization algorithm. Neural Computing and Applications. 34(21). 18341–18368. 6 indexed citations
4.
Dökeroğlu, Tansel & Ender Sevinç. (2021). Memetic Teaching–Learning-Based Optimization algorithms for large graph coloring problems. Engineering Applications of Artificial Intelligence. 102. 104282–104282. 22 indexed citations
5.
Sevinç, Ender. (2019). A Novel Evolutionary Algorithm for Data Classification Problem With Extreme Learning Machines. IEEE Access. 7. 122419–122427. 16 indexed citations
6.
Sevinç, Ender & Tansel Dökeroğlu. (2019). A novel hybrid teaching-learning-based optimization algorithm for the classification of data by using extreme learning machines. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 1523–1533. 15 indexed citations
7.
Dökeroğlu, Tansel, Ender Sevinç, & Ahmet Coşar. (2019). Artificial bee colony optimization for the quadratic assignment problem. Applied Soft Computing. 76. 595–606. 74 indexed citations
8.
Sevinç, Ender & Tansel Dökeroğlu. (2019). A novel parallel local search algorithm for the maximum vertex weight clique problem in large graphs. Soft Computing. 24(5). 3551–3567. 7 indexed citations
9.
Sevinç, Ender. (2019). The Effect of Hidden Neurons in Single-Hidden Layer Feedforward Neural Networks. Bilişim Teknolojileri Dergisi. 12(4). 277–286. 2 indexed citations
10.
Dökeroğlu, Tansel, Ender Sevinç, Tayfun Küçükyılmaz, & Ahmet Coşar. (2019). A survey on new generation metaheuristic algorithms. Computers & Industrial Engineering. 137. 106040–106040. 649 indexed citations breakdown →
11.
Dökeroğlu, Tansel & Ender Sevinç. (2019). Evolutionary parallel extreme learning machines for the data classification problem. Computers & Industrial Engineering. 130. 237–249. 20 indexed citations
12.
Sevinç, Ender. (2018). ACTIVATION FUNCTIONS IN SINGLE HIDDEN LAYER FEED-FORWARD NEURAL NETWORKS. 1–13. 2 indexed citations
13.
Karakaya, Murat & Ender Sevinç. (2017). An Efficient Genetic Algorithm for Routing Multiple UAVs under Flight Range and Service Time Window Constraints. Bilişim Teknolojileri Dergisi. 10(1). 113. 7 indexed citations
14.
Sevinç, Ender & Murat Karakaya. (2014). Maximizing UAV Target Coverage under Flight Range and Target Service Time Constraints. 3(4). 290–294. 1 indexed citations
15.
Yurtseven, H. & Ender Sevinç. (2013). Pressure Dependence of the Thermodynamic Quantities in Phase II of Solid Benzene. High Temperature Materials and Processes. 32(5). 421–425. 3 indexed citations
16.
Sevinç, Ender & Ahmet Coşar. (2010). An Evolutionary Genetic Algorithm for Optimization of Distributed Database Queries. The Computer Journal. 54(5). 717–725. 40 indexed citations
17.
Sevinç, Ender & Ahmet Coşar. (2009). An evolutionary genetic algorithm for optimization of distributed database queries. OpenMETU (Middle East Technical University). 2. 147–152. 3 indexed citations
18.
Doğaç, Asuman, et al.. (2000). Dynamic modification of XML documents. ACM SIGecom Exchanges. 1(1). 1–6. 3 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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