Adil Bagirov

4.1k citations
134 papers · 2.5k indexed · h-index 28

Adil Bagirov

121 papers receiving 2.3k citations

Peers

Adil Bagirov
Comparison fields: 5 of 133
  • Numerical Analysis 669
  • Computational Theory and Mathematics 726
  • Artificial Intelligence 875
  • Computer Vision and Pattern Recognition 468
  • Computational Mechanics 423
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Countries citing papers authored by Adil Bagirov

Since Specialization
Citations

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

Fields of papers citing papers by Adil Bagirov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Adil Bagirov, 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 Adil Bagirov Line = papers co-authored together Adil Bagirov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20230
3 20212
4 20216
5 201911
6 20193
7 20187
8 201741
9
CONTINUOUS SUBDIFFERENTIAL APPROXIMATION AND ITS CONSTRUCTION
20150
10
A novel approach to optimal pump scheduling in water distribution systems
20122
11
Application of Optimisation-Based Data Mining Techniques to Medical Data Sets: A Comparative Analysis
20121
12
Comparison of metaheuristic algorithms for pump operation optimization
20123
13
Minimization of pumping costs in water distribution systems using explicit and implicit pump scheduling
20121
14
Improving naive Bayes classifier using conditional probabilities
201118
15
Cluster analysis of a tobacco control data set
20101
16
A generalized subgradient method with piecewise linear subproblem
20102
17
A new modified global k-means algorithm for clustering large data sets
20092
18 20079
19
Optimization based clustering algorithms in Multicast group Hierarchies
20030
20
A method of approximating a quasidifferential
199214

About Adil Bagirov

Adil Bagirov is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Artificial Intelligence, having authored 134 papers that have together received 2.5k indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (39 papers), Face and Expression Recognition (27 papers), Advanced Clustering Algorithms Research (26 papers), Optimization and Variational Analysis (20 papers), Sparse and Compressive Sensing Techniques (15 papers), Metaheuristic Optimization Algorithms Research (12 papers), Water Systems and Optimization (11 papers) and Water resources management and optimization (9 papers). The work is most often cited by research in Numerical Analysis (669 citations), Computational Theory and Mathematics (726 citations) and Artificial Intelligence (875 citations). Adil Bagirov has collaborated with scholars based in Australia, Finland and Türkiye. Frequent co-authors include Napsu Karmitsa, Julien Ugon, John Yearwood, Marko M. Mäkelä, A. M. Rubinov, Sona Taheri, Nargiz Sultanova, Andrew Barton, Dean Webb and Ramiz M. Aliguliyev. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and IEEE Transactions on Information Theory.

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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