Prabhat Ranjan Singh

455 citations
12 papers · 315 · h-index 8

Impact in

Papers in

Prabhat Ranjan Singh

12 papers receiving 302 citations

Peers

Prabhat Ranjan Singh
Comparison fields: 5 of 57
  • Computer Networks and Communications 139
  • Information Systems 118
  • Artificial Intelligence 94
  • Computational Theory and Mathematics 43
  • Hardware and Architecture 14
Replace S. Kannan with:
S. Kannan India
K.P.N Jayasena Sri Lanka
K. Selvakumar India
Niki Pissinou United States
Rafik Bouaziz Tunisia
Mirjana D. Stojanović Serbia
Suresh Kumar India
Mehdi Golsorkhtabaramiri Iran
Youcef Gheraibia United Kingdom
Poria Pirozmand China
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Citations per field
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S. Kannan · 1×
Citations per year

Countries citing papers authored by Prabhat Ranjan Singh

Since Specialization
Citations

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

Fields of papers citing papers by Prabhat Ranjan Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prabhat Ranjan Singh. 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 Prabhat Ranjan Singh. The network helps show where Prabhat Ranjan Singh may publish in the future.

Co-authors

The 13 scholars most cited alongside Prabhat Ranjan Singh, 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 Prabhat Ranjan Singh Line = papers co-authored together Prabhat Ranjan Singh links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2018131
2 201844
3 202340
4 201935
5 202321
6 202311
7 201411
8 20148
9 20194
10 20134
11 20233
12 20193

About Prabhat Ranjan Singh

Prabhat Ranjan Singh is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications and Cognitive Neuroscience, having authored 12 papers that have together received 315 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (3 papers), IoT and Edge/Fog Computing (2 papers), Parallel Computing and Optimization Techniques (2 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), Evolutionary Algorithms and Applications (2 papers), Low-power high-performance VLSI design (2 papers), Aesthetic Perception and Analysis (2 papers) and Analog and Mixed-Signal Circuit Design (2 papers). The work is most often cited by research in Computer Networks and Communications (139 citations), Information Systems (118 citations), Artificial Intelligence (94 citations), Computational Theory and Mathematics (43 citations) and Hardware and Architecture (14 citations). Prabhat Ranjan Singh has collaborated with scholars based in China, India and Egypt. Frequent co-authors include Rahul Yadav, Shengwu Xiong, Mohamed Abd Elaziz, Yu‐Chu Tian, Ibrahim A. Elgendy, Weizhe Zhang, Omprakash Kaiwartya, Vivek Kumar Singh, Teerath Das and Tanesh Kumar. Their work appears in journals such as IEEE Access, Applied Soft Computing, Energy Reports, Expert Systems with Applications and Lecture notes in networks and systems.

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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