A. M. Nagy

1.0k citations
40 papers · 830 · h-index 16

Impact in

    • Fractional Differential Equations Solutions
    • Differential Equations and Numerical Methods
    • Iterative Methods for Nonlinear Equations
    • Numerical methods for differential equations

Papers in

    • Fractional Differential Equations Solutions 36
    • Iterative Methods for Nonlinear Equations 10
    • Differential Equations and Numerical Methods 10
    • Numerical methods for differential equations 8

A. M. Nagy

39 papers receiving 776 citations

Peers

A. M. Nagy
Comparison fields: 5 of 61
  • Modeling and Simulation 636
  • Numerical Analysis 405
  • Applied Mathematics 234
  • Statistical and Nonlinear Physics 183
  • Control and Systems Engineering 148
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Citations per field
00.5×10×14.3×
Babak Shiri · 1×
Citations per year

Countries citing papers authored by A. M. Nagy

Since Specialization
Citations

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

Fields of papers citing papers by A. M. Nagy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside A. M. Nagy, 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 A. M. Nagy Line = papers co-authored together A. M. Nagy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010138
2 201576
3 201558
4 201855
5 201451
6 201750
7 201636
8 201931
9 201830
10 201930
11 201725
12 201620
13 201319
14 202019
15 202319
16 202216
17 202115
18 201614
19 202313
20 201812

About A. M. Nagy

A. M. Nagy is a scholar working on Modeling and Simulation, Numerical Analysis, Applied Mathematics, Computer Networks and Communications and Control and Systems Engineering, having authored 40 papers that have together received 830 indexed citations. Recurring topics across this work include Fractional Differential Equations Solutions (36 papers), Nonlinear Differential Equations Analysis (13 papers), Iterative Methods for Nonlinear Equations (10 papers), Differential Equations and Numerical Methods (10 papers), Numerical methods for differential equations (8 papers), Advanced Control Systems Design (7 papers), Neural Networks Stability and Synchronization (6 papers) and Nonlinear Waves and Solitons (5 papers). The work is most often cited by research in Modeling and Simulation (636 citations), Numerical Analysis (405 citations), Applied Mathematics (234 citations), Statistical and Nonlinear Physics (183 citations) and Control and Systems Engineering (148 citations). A. M. Nagy has collaborated with scholars based in Egypt, Kuwait and Saudi Arabia. Frequent co-authors include N. H. Sweilam, Adel A. El‐Sayed, Abdellatif Ben Makhlouf, M. M. Khader, Omar Naifar, Manh Tuan Hoang, A‎. ‎M‎. ‎A‎. El-Sayed, Assaad Jmal, Sumati Kumari Panda and Mohamed Ali Hammami. Their work appears in journals such as Chaos Solitons & Fractals, Applied Mathematics and Computation, ACM Transactions on Mathematical Software, Scientific Reports and Journal of Computational and Nonlinear Dynamics.

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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