Najme Mansouri

2.1k total citations
104 papers, 1.4k citations indexed

About

Najme Mansouri is a scholar working on Computer Networks and Communications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Najme Mansouri has authored 104 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Computer Networks and Communications, 44 papers in Information Systems and 30 papers in Artificial Intelligence. Recurrent topics in Najme Mansouri's work include Cloud Computing and Resource Management (44 papers), IoT and Edge/Fog Computing (34 papers) and Distributed and Parallel Computing Systems (26 papers). Najme Mansouri is often cited by papers focused on Cloud Computing and Resource Management (44 papers), IoT and Edge/Fog Computing (34 papers) and Distributed and Parallel Computing Systems (26 papers). Najme Mansouri collaborates with scholars based in Iran, United States and Algeria. Najme Mansouri's co-authors include Mohammad Masoud Javidi, Behnam Mohammad Hasani Zade, Süleyman Tosun, Ercüment Arvas, Mahmut Kandemir, Marjan Kuchaki Rafsanjani, Khaled Goher, Sulaiman O. Fadlallah, Young Sik Kim and W. Hung and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Computers & Industrial Engineering.

In The Last Decade

Najme Mansouri

93 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Najme Mansouri Iran 22 945 810 253 206 169 104 1.4k
Marcello Cinque Italy 18 775 0.8× 441 0.5× 321 1.3× 106 0.5× 159 0.9× 122 1.1k
Yong Meng Teo Singapore 18 763 0.8× 467 0.6× 148 0.6× 183 0.9× 109 0.6× 105 1.2k
Ming Zhao United States 20 1.4k 1.5× 1.0k 1.3× 272 1.1× 264 1.3× 185 1.1× 99 1.7k
Abdelmadjid Bouabdallah France 13 842 0.9× 541 0.7× 410 1.6× 76 0.4× 291 1.7× 24 1.3k
Shu Yin United States 16 677 0.7× 639 0.8× 116 0.5× 101 0.5× 79 0.5× 65 990
G. Nordstrom United States 8 443 0.5× 344 0.4× 442 1.7× 197 1.0× 215 1.3× 14 1.2k
Guiran Chang China 16 920 1.0× 616 0.8× 280 1.1× 46 0.2× 218 1.3× 111 1.2k
Daya Gupta India 20 556 0.6× 569 0.7× 497 2.0× 45 0.2× 217 1.3× 116 1.2k
Zahra Pooranian Italy 20 755 0.8× 333 0.4× 253 1.0× 46 0.2× 286 1.7× 37 1.1k
Peter Kilpatrick United Kingdom 14 565 0.6× 371 0.5× 288 1.1× 149 0.7× 104 0.6× 85 866

Countries citing papers authored by Najme Mansouri

Since Specialization
Citations

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

Fields of papers citing papers by Najme Mansouri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Najme Mansouri

This figure shows the co-authorship network connecting the top 25 collaborators of Najme Mansouri. A scholar is included among the top collaborators of Najme Mansouri 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 Najme Mansouri. Najme Mansouri 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.
Mansouri, Najme, et al.. (2025). Reinforcement learning-based solution for resource management in fog computing: A comprehensive survey. Expert Systems with Applications. 276. 127214–127214. 2 indexed citations
2.
Yaghoobi, Mohammad Ali, et al.. (2025). A dual-phase strategy for clustering: integrating genetic algorithms with tabu search. Knowledge and Information Systems. 67(12). 12211–12266.
3.
Zade, Behnam Mohammad Hasani, et al.. (2024). Multi-objective feature selection algorithm using Beluga Whale Optimization. Chemometrics and Intelligent Laboratory Systems. 257. 105295–105295. 2 indexed citations
4.
Mansouri, Najme, et al.. (2024). Optimal feature selection through reinforcement learning and fuzzy signature for improving classification accuracy. Multimedia Tools and Applications. 84(10). 6931–6965.
5.
Mansouri, Najme, et al.. (2024). A novel energy-based task scheduling in fog computing environment: an improved artificial rabbits optimization approach. Cluster Computing. 27(6). 8413–8458. 10 indexed citations
6.
Mansouri, Najme, et al.. (2024). A Binary Chaotic Transient Search Optimization Algorithm for Enhancing Feature Selection. Arabian Journal for Science and Engineering. 50(2). 679–702. 4 indexed citations
7.
Mansouri, Najme, et al.. (2024). Deep reinforcement learning-based scheduling in distributed systems: a critical review. Knowledge and Information Systems. 66(10). 5709–5782. 16 indexed citations
8.
Mansouri, Najme, et al.. (2024). Correction to: Deep learning approaches to detect breast cancer: a comprehensive review. Multimedia Tools and Applications. 84(21). 24191–24192.
9.
Zade, Behnam Mohammad Hasani, Najme Mansouri, & Mohammad Masoud Javidi. (2024). Multi-objective task scheduling based on PSO-Ring and intuitionistic fuzzy set. Cluster Computing. 27(8). 11747–11802. 5 indexed citations
10.
Mansouri, Najme, et al.. (2024). A Comprehensive Survey of Multi-Level Thresholding Segmentation Methods for Image Processing. Archives of Computational Methods in Engineering. 31(6). 3647–3697. 33 indexed citations
11.
12.
Mansouri, Najme, et al.. (2021). A Fuzzy based Pathfinder Optimization Technique for Performance-Effective Task Scheduling in Cloud. SHILAP Revista de lepidopterología. 1 indexed citations
13.
Mansouri, Najme & Mohammad Masoud Javidi. (2019). A Review of Replica Replacement Techniques in Grid Computing and Cloud Computing. 51(2). 134–151. 3 indexed citations
14.
Mansouri, Najme & Mohammad Masoud Javidi. (2019). Improving Data Availability Using Combined Replication Strategy in Cloud Environment. SHILAP Revista de lepidopterología. 1 indexed citations
15.
Mansouri, Najme & Mohammad Masoud Javidi. (2018). An Efficient Data Replication Strategy in Large-Scale Data Grid Environments Based on Availability and Popularity. SHILAP Revista de lepidopterología. 50(1). 39–50. 1 indexed citations
16.
Mansouri, Najme. (2016). A Utility-Based Data Replication Algorithm in Large Scale Data Grids. 7(4). 79–93. 2 indexed citations
17.
Mansouri, Najme, et al.. (2014). IMPROVING DATA GRIDS PERFORMANCE BY USING MODIFIED DYNAMIC HIERARCHICAL REPLICATION STRATEGY. 10(1). 27–37. 1 indexed citations
18.
Mansouri, Najme. (2013). A Threshold-based Dynamic Data Replication and Parallel Job Scheduling strategy to enhance Data Grid. Cluster Computing. 17(3). 957–977. 16 indexed citations
19.
Mansouri, Najme, et al.. (2007). Speech Recognition via Lyapunov Metrics Using Neuro-Fuzzy Models. 1 indexed citations
20.
Mansouri, Najme & J. P. Kernévez. (1998). Estimation of parameters in nonlinear problems. Numerical Algorithms. 17(3-4). 333–343. 2 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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