Saeed Ketabchi

449 total citations
35 papers, 318 citations indexed

About

Saeed Ketabchi is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, Saeed Ketabchi has authored 35 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Numerical Analysis, 16 papers in Computational Theory and Mathematics and 12 papers in Control and Systems Engineering. Recurrent topics in Saeed Ketabchi's work include Advanced Optimization Algorithms Research (23 papers), Optimization and Variational Analysis (9 papers) and Face and Expression Recognition (6 papers). Saeed Ketabchi is often cited by papers focused on Advanced Optimization Algorithms Research (23 papers), Optimization and Variational Analysis (9 papers) and Face and Expression Recognition (6 papers). Saeed Ketabchi collaborates with scholars based in Iran, Czechia and United States. Saeed Ketabchi's co-authors include Hossein Moosaei, Saeed Fallahi, Pãnos M. Pardalos, A. Ghanadzadeh, H. Ghanadzadeh, Maziar Salahi, Milan Hladík, M. Tanveer, Mehdi Razzaghi and Hamed Jafari and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers & Operations Research and Applied Mathematics and Computation.

In The Last Decade

Saeed Ketabchi

33 papers receiving 306 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saeed Ketabchi Iran 12 169 143 77 61 50 35 318
Detong Zhu China 12 293 1.7× 213 1.5× 98 1.3× 53 0.9× 106 2.1× 84 450
Qin Ni China 11 186 1.1× 212 1.5× 39 0.5× 19 0.3× 30 0.6× 54 425
Dmitriy Drusvyatskiy United States 11 164 1.0× 202 1.4× 36 0.5× 15 0.2× 19 0.4× 37 319
Masoud Ahookhosh Austria 13 362 2.1× 204 1.4× 104 1.4× 38 0.6× 62 1.2× 29 480
Jinkui Liu China 9 243 1.4× 93 0.7× 18 0.2× 56 0.9× 15 0.3× 29 340
Ying Cui United States 11 112 0.7× 114 0.8× 43 0.6× 44 0.7× 26 0.5× 27 297
Carl A. Schweiger United States 5 256 1.5× 265 1.9× 142 1.8× 14 0.2× 216 4.3× 7 527
Mahmoud El-Alem Egypt 10 242 1.4× 213 1.5× 57 0.7× 8 0.1× 96 1.9× 24 358
Xinyuan Zhao China 8 219 1.3× 177 1.2× 44 0.6× 25 0.4× 29 0.6× 24 374
Aleksandr Moiseevich Rubinov Australia 5 193 1.1× 214 1.5× 35 0.5× 14 0.2× 56 1.1× 6 363

Countries citing papers authored by Saeed Ketabchi

Since Specialization
Citations

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

Fields of papers citing papers by Saeed Ketabchi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saeed Ketabchi

This figure shows the co-authorship network connecting the top 25 collaborators of Saeed Ketabchi. A scholar is included among the top collaborators of Saeed Ketabchi 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 Saeed Ketabchi. Saeed Ketabchi 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.
Hladík, Milan, et al.. (2025). An overview of absolute value equations: from theory to solution methods and challenges. Computational Optimization and Applications. 93(1). 435–488.
2.
Moosaei, Hossein, et al.. (2023). Newton-based approach to solving K-SVCR and Twin-KSVC multi-class classification in the primal space. Computers & Operations Research. 160. 106370–106370. 2 indexed citations
3.
Ketabchi, Saeed, et al.. (2021). Smooth augmented Lagrangian method for twin bounded support vector machine. Numerical Algebra Control and Optimization. 12(4). 659–659. 1 indexed citations
4.
Moosaei, Hossein, Saeed Ketabchi, Mehdi Razzaghi, & M. Tanveer. (2021). Generalized Twin Support Vector Machines. Neural Processing Letters. 53(2). 1545–1564. 18 indexed citations
5.
Ketabchi, Saeed, Hossein Moosaei, & Milan Hladík. (2021). On the minimum-norm solution of convex quadratic programming. RAIRO - Operations Research. 55(1). 247–260. 1 indexed citations
6.
Ketabchi, Saeed, et al.. (2021). Optimal correction of infeasible equations system as Ax + B|x|= b using ℓ p-norm regularization. Boletim da Sociedade Paranaense de Matemática. 40. 1–16. 1 indexed citations
7.
Ketabchi, Saeed, et al.. (2020). DC programming and DCA for parametric-margin ν-support vector machine. Applied Intelligence. 50(6). 1763–1774. 14 indexed citations
8.
Ketabchi, Saeed, et al.. (2019). Numerical comparisons of smoothing functions for optimal correction of an infeasible system of absolute value equations. Numerical Algebra Control and Optimization. 10(1). 13–21. 16 indexed citations
9.
Ketabchi, Saeed, et al.. (2018). $$l_{p}$$ l p -Norm Regularization Method $$ (0<p<1) $$ ( 0 < p < 1 ) and DC Programming for Correction System of Inconsistency Linear Inequalities. Bulletin of the Iranian Mathematical Society.. 45(3). 865–882. 2 indexed citations
10.
Salkuyeh, Davod Khojasteh, et al.. (2018). On the solution of the fully fuzzy Sylvester matrix equation. International Journal of Modelling and Simulation. 40(1). 80–85. 4 indexed citations
11.
Ketabchi, Saeed, et al.. (2017). Computing minimum norm solution of linear systems of equations by the generalized Newton method. Numerical Algebra Control and Optimization. 7(2). 113–119. 2 indexed citations
12.
Ketabchi, Saeed, et al.. (2017). An improvement on parametric $$\nu $$ ν -support vector algorithm for classification. Annals of Operations Research. 276(1-2). 155–168. 19 indexed citations
13.
Ketabchi, Saeed, et al.. (2015). On the Solution of a Nonconvex Fractional Quadratic Problem. SHILAP Revista de lepidopterología. 1 indexed citations
14.
Moosaei, Hossein, et al.. (2015). Some techniques for solving absolute value equations. Applied Mathematics and Computation. 268. 696–705. 19 indexed citations
15.
Ketabchi, Saeed, et al.. (2014). Parametric approach for correcting inconsistent linear equality system. Optimization methods & software. 29(6). 1317–1322. 4 indexed citations
16.
Ketabchi, Saeed, et al.. (2013). Augmented Lagrangian method for recourse problem of two-stage stochastic linear programming. Kybernetika. 49(1). 188–198. 2 indexed citations
17.
Ketabchi, Saeed & Hossein Moosaei. (2012). An efficient method for optimal correcting of absolute value equations by minimal changes in the right hand side. Computers & Mathematics with Applications. 64(6). 1882–1885. 31 indexed citations
18.
Ketabchi, Saeed, Hossein Moosaei, & Saeed Fallahi. (2011). Optimal error correction of the absolute value equation using a genetic algorithm. Mathematical and Computer Modelling. 57(9-10). 2339–2342. 15 indexed citations
19.
Ketabchi, Saeed, Hossein Moosaei, & Saeed Fallahi. (2010). Optimal Correction of Infeasible System in Linear Equality via Genetic Algorithm. Applications and Applied Mathematics: An International Journal (AAM). 5(2). 18. 1 indexed citations
20.
Ketabchi, Saeed, et al.. (2006). On the solution set of convex problems and its numerical application. Journal of Computational and Applied Mathematics. 206(1). 288–292. 6 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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