Saeid Barshandeh

1.1k total citations · 2 hit papers
13 papers, 804 citations indexed

About

Saeid Barshandeh is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Saeid Barshandeh has authored 13 papers receiving a total of 804 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Electrical and Electronic Engineering and 4 papers in Computer Networks and Communications. Recurrent topics in Saeid Barshandeh's work include Metaheuristic Optimization Algorithms Research (8 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Indoor and Outdoor Localization Technologies (3 papers). Saeid Barshandeh is often cited by papers focused on Metaheuristic Optimization Algorithms Research (8 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Indoor and Outdoor Localization Technologies (3 papers). Saeid Barshandeh collaborates with scholars based in Iran, Czechia and Türkiye. Saeid Barshandeh's co-authors include Benyamın Abdollahzadeh, Farhad Soleimanian Gharehchopogh, Pavel Trojovský, Farhad Soleimanian Gharehchopogh, Laith Abualigah, El‐Sayed M. El‐kenawy, Seyedali Mirjalili, Nima Khodadadi, Bahman Arasteh and Mohammad Masdari and has published in prestigious journals such as Applied Soft Computing, Knowledge-Based Systems and International Journal of Intelligent Systems.

In The Last Decade

Saeid Barshandeh

13 papers receiving 770 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning

2024 240 citations Benyamın Abdollahzadeh, Nima Khodadadi et al. Cluster Computing profile →
A multi-objective mutation-based dynamic Harris Hawks optimization for botnet detection in IoT

2023 103 citations Farhad Soleimanian Gharehchopogh, Benyamın Abdollahzadeh et al. Internet of Things profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Saeid Barshandeh Iran	11	438	185	154	148	99	13	804
Shaoqiu Zheng China	14	516 1.2×	117 0.6×	220 1.4×	125 0.8×	162 1.6×	20	899
Ranjith Kumar A India	4	359 0.8×	203 1.1×	133 0.9×	151 1.0×	83 0.8×	8	812
Itziar Landa-Torres Spain	14	323 0.7×	134 0.7×	136 0.9×	162 1.1×	99 1.0×	28	829
Ali Asghar Pourhaji Kazem Iran	9	338 0.8×	297 1.6×	131 0.9×	174 1.2×	91 0.9×	22	905
Andreas Janecek Austria	11	367 0.8×	101 0.5×	126 0.8×	115 0.8×	154 1.6×	21	795
Nitish Chopra India	8	338 0.8×	129 0.7×	147 1.0×	212 1.4×	100 1.0×	10	785
Jianji Ren China	13	297 0.7×	206 1.1×	93 0.6×	224 1.5×	72 0.7×	33	739
Bin-Yih Liao Taiwan	12	301 0.7×	211 1.1×	104 0.7×	155 1.0×	209 2.1×	33	752
Guo Zhou China	16	375 0.9×	101 0.5×	157 1.0×	99 0.7×	80 0.8×	39	713

Countries citing papers authored by Saeid Barshandeh

Since Specialization

Citations

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

Fields of papers citing papers by Saeid Barshandeh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saeid Barshandeh

This figure shows the co-authorship network connecting the top 25 collaborators of Saeid Barshandeh. A scholar is included among the top collaborators of Saeid Barshandeh 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 Saeid Barshandeh. Saeid Barshandeh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

Abdollahzadeh, Benyamın, Nima Khodadadi, Saeid Barshandeh, et al.. (2024). Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning. Cluster Computing. 27(4). 5235–5283. 240 indexed citations breakdown →

Barshandeh, Saeid, et al.. (2023). A learning-based metaheuristic administered positioning model for 3D IoT networks. Applied Soft Computing. 136. 110113–110113. 7 indexed citations

Gharehchopogh, Farhad Soleimanian, Benyamın Abdollahzadeh, Saeid Barshandeh, & Bahman Arasteh. (2023). A multi-objective mutation-based dynamic Harris Hawks optimization for botnet detection in IoT. Internet of Things. 24. 100952–100952. 103 indexed citations breakdown →

Pinho, Pedro, Kambiz Majidzadeh, Ch. Ghobadi, et al.. (2023). Dual-Band Planar Microstrip Monopole Antenna Design Using Multi-Objective Hybrid Optimization Algorithm. 467–475. 3 indexed citations

Gharehchopogh, Farhad Soleimanian, Mohammad H. Nadimi-Shahraki, Saeid Barshandeh, Benyamın Abdollahzadeh, & Hoda Zamani. (2022). CQFFA: A Chaotic Quasi-oppositional Farmland Fertility Algorithm for Solving Engineering Optimization Problems. Journal of Bionic Engineering. 20(1). 158–183. 72 indexed citations

Barshandeh, Saeid, et al.. (2021). A learning automata-based hybrid MPA and JS algorithm for numerical optimization problems and its application on data clustering. Knowledge-Based Systems. 236. 107682–107682. 38 indexed citations

Abdollahzadeh, Benyamın, et al.. (2021). An enhanced binary slime mould algorithm for solving the 0–1 knapsack problem. Engineering With Computers. 38(S4). 3423–3444. 36 indexed citations

Barshandeh, Saeid, et al.. (2021). A range‐free localization algorithm for IoT networks. International Journal of Intelligent Systems. 37(12). 10336–10379. 24 indexed citations

Barshandeh, Saeid, et al.. (2020). A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems. Engineering With Computers. 37(4). 3079–3122. 103 indexed citations

10.

Abdollahzadeh, Benyamın, Farhad Soleimanian Gharehchopogh, & Saeid Barshandeh. (2020). Discrete farmland fertility optimization algorithm with metropolis acceptance criterion for traveling salesman problems. International Journal of Intelligent Systems. 36(3). 1270–1303. 58 indexed citations

11.

Shahidinejad, Ali & Saeid Barshandeh. (2020). Sink selection and clustering using fuzzy‐based controller for wireless sensor networks. International Journal of Communication Systems. 33(15). 20 indexed citations

12.

Barshandeh, Saeid, et al.. (2020). HMPA: an innovative hybrid multi-population algorithm based on artificial ecosystem-based and Harris Hawks optimization algorithms for engineering problems. Engineering With Computers. 38(2). 1581–1625. 62 indexed citations

13.

Masdari, Mohammad & Saeid Barshandeh. (2020). Discrete teaching–learning-based optimization algorithm for clustering in wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing. 11(11). 5459–5476. 38 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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